Illicit Financial Flows
and the Problem of Net Resource Transfers from Africa: 1980-2009
Joint Report by
African Development Bank and Global Financial Integrity May 2013
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
Joint Report by
African Development Bank and Global Financial Integrity May 2013
Copyright © Text and Graphics: 2013 the African Development Bank (AfDB) and Global Financial Integrity (GFI) All rights reserved. The text and data in this publication may be reproduced as long as the source is clearly cited. Reproduction for commercial purposes is forbidden. The publication was jointly produced by the African Development Bank and Global Financial Integrity. Global Financial Integrity is a program of the Center for International Policy.
Foreword May 29, 2013 We are pleased to present to you this report on “Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009.” Today, with good resource husbandry, Africa could be in a position to finance the bulk of its development needs from its own resources, with external financing as a merely complementary source. But as long as the African continent continues to witness illicit resource transfers of the order of magnitude described in this study, domestic financing for development will continue to be seriously inadequate. The report finds that during the thirty years covered by the study, Africa provided net resources to the world of up to US$1.4 trillion on a cumulative basis, far exceeding inflows over the same period. The illicit hemorrhage of resources from Africa is therefore about four times Africa’s current external debt and almost equivalent to Africa’s current GDP. In recent years, African leaders have shown increasing interest on the issues of illicit financial flows and its corollary, stolen asset recovery. The interest ranges from the political changes brought about by the Arab Spring in North Africa, with citizens demanding the return of stolen assets, to the political debates heightened by the natural resource boom in Sub-Saharan African countries. In all these cases, there are popular demands for more transparent processes and the avoidance of capture by the elites of the rents from natural resource exploitation and other sources of public revenue. The irony of Africa being richly endowed with natural resources but continuing to depend on external support for the provision of basic services is beginning to dawn on many African countries. A number of them have joined the Extractive Industries Transparency Initiative, while others have introduced over-arching legislation to plug financing loopholes. Illicit financial flows are a global problem and will require concerted efforts from the international community and the involvement of individual African countries. Many international institutions—the African Development Bank, G20, UN, European Union Commission, African Union Commission, World Bank, International Monetary Fund, and Bank for International Settlements—have underlined the importance of a determined and collective approach to resolving the challenges posed by the global shadow economy, comprising tax havens, secrecy jurisdictions, disguised corporations, trade mispricing, and money laundering. The chances of success will increase markedly if African
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
c
governments themselves take domestic measures to address corruption, strengthen their antimoney laundering efforts, and also improve their investment codes. None of these is technically difficult, but they all require political will for success. The resources lost to Africa from illicit financial outflows are large. If harnessed, they could plug the financing deficit that afflicts the continent, enable countries to extend their socio-economic infrastructure, create employment for their youthful populations, and safeguard their natural resource revenues. We should therefore accord efforts to address the proliferation of illicit financial flows from Africa as much importance as we are putting on domestic resource mobilization and the attraction of foreign direct investment.
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Donald Kaberuka
Raymond Baker
President
Director
African Development Bank Group
Global Financial Integrity
Tunis, Tunisia
Washington, DC
African Development Bank and Global Financial Integrity
Acknowledgements This report on “Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009” was prepared by a joint team comprised of Dev Kar, Lead Economist, Sarah Freitas, Economist, from Global Financial Integrity and Jennifer Mbabazi Moyo, Senior Economist and Guirane Samba Ndiaye, Economist from the African Development Bank. The work was carried out under the general direction of Mthuli Ncube, Chief Economist and Vice President, Steve KayizziMugerwa, Director, Development Research Department, and Issa Faye, Manager, Development Research Department, (EDRE1), African Development Bank and Tom Cardamone, Managing Director, and Raymond Baker, Director, Global Financial Integrity. Our gratitude goes to the authors for their outstanding work on this analysis. We are similarly grateful to all staff from our institutions who have worked so hard to make this joint report possible and who have provided comments at different stages of the report preparation. In particular, we thank Barbara Barungi, Ralf Kruger, Peter Sturmheit, Walter Odero, Charles Toto Same, Ousmane Dore, and Joel Muzima from the African Development Bank and Crystal Nwaroh and Julianna Flanagan, economics interns from Global Financial Integrity.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
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Notes: a. The findings, interpretations, and conclusions expressed herein are those of the authors and do not necessarily reflect the views of the Executive Directors of the African Development Bank, (or the governments they represent) and Global Financial Integrity. b. The African Development Bank and the Global Financial Integrity do not guarantee accuracy of the data included in this work. The boundaries, colors, denominations, and any information shown on any map in this work does not imply any judgment on the part of the African Development Bank or the Global Financial Integrity concerning the legal status of any territory or the endorsement or acceptance of such boundaries. c. The terms country and nation (or national) as used in this report do not in all cases refer to a territorial entity that is a state as understood by international law and practice. The terms cover well-defined, geographically self-contained economic areas that may not be states but for which statistical data are maintained on a separate and independent basis.
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African Development Bank and Global Financial Integrity
Table of Contents Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 II. Methodological Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 i. Key Definitions and Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 ii. Overall Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 a. Data Issues for Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1. Choice of Time Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2. Strategy for Dealing with Missing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 III. Net Recorded Transfers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 i. Narrow Measure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 ii. Broad Measure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 IV. Illicit Financial Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 i. Methods of Estimating Illicit Financial Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 ii. Trends in Illicit Financial Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 iii. Estimating the Severity of Illicit Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 a. Volume of Outflows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 b. Illicit Flows to GDP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 c. Illicit Flows to External Debt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 d. Illicit Flows to Official Development Assistance (ODA) . . . . . . . . . . . . . . . . . . . . . . . . . . 27 e. Illicit Flows to Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 f. Illicit Flows to Non-oil Exports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 V. Net Resource Transfers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 VI. Policy Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 i. Policies to Restrict the Absorption of Illicit Financial Flows . . . . . . . . . . . . . . . . . . . . . . . . . 43 a. Promote Transparency in Global Financial System . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 b. Automatic Exchange of Tax Information (AEI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 c. Double Tax Avoidance Agreements (DTAA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 ii. Policies to Curtail Illicit Financial Outflows from Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 a. Resource Rich Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 b. Resource Poor Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 iii. Boosting Net Recorded Transfers by Improving the Business Climate . . . . . . . . . . . . . . . . 48 VII. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
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List of Boxes Box 1: Box 2: Box 3: Box 4: Box 5: Box 6:
Defining Net Recorded Transfers (NRecT) and Net Resource Transfers (NRT) . . . . . . . . . . Normalization of Illicit Financial Flows (IFF) estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The World Bank Residual Method (Change in External Debt (CED)) . . . . . . . . . . . . . . . . . . . Trade Mispricing (Gross Excluding Reversals (GER)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Curtailing Illicit Financial Flows as a Development Strategy . . . . . . . . . . . . . . . . . . . . . . . . . The Open Budget Initiative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11 11 22 22 29 46
List of Figures and Maps Chart 1. Chart 2. Chart 3. Chart 4. Charts 5. Chart 6. Chart 7. Chart 8. Chart 9. Chart 10. Chart 11. Chart 12.
Top Five Gainers and Losers of Real Net Recorded Transfers Narrow, Cumulative 1980-2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Top Five Gainers and Losers of Real Net Recorded Transfers Broad, Cumulative 1980-2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Africa: Real Illicit Financial Flows, 1980-2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Distribution of Real Non-normalized Illicit Financial Flows, Cumulative 1980-2009 . . . . 25 Top 20 Countries’ Non-normalized Illicit Financial Flows, Charts a-f . . . . . . . . . . . . 26-30 Africa: Alternative Indicators of Real Net Resource Transfers: 1980-2009 . . . . . . . . . . . 34 Decennial Shifts in NRT, North Africa vs. Sub-Saharan Africa . . . . . . . . . . . . . . . . . . . . 36 Decennial Shifts in NRT within Sub-Saharan Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Distribution of Cumulative NRT, North Africa vs. Sub-Saharan Africa, 1980-2009 . . . . 37 Distribution of Cumulative NRT within Sub-Saharan Africa, 1980-2009 . . . . . . . . . . . . 37 Asymmetrical Distribution of Cumulative Real Broad Net Resource Transfers, 1980-2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Cumulative Real Net Resource Transfers, 1980-to-2009 . . . . . . . . . . . . . . . . . . . . . . . . 40
List of Tables Table 1. Table 2. Table 3.
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Africa: Decennial Developments in Real Non-normalized Illicit Financial Flows . . . . . . 24 Africa: Decennial Developments in Real Normalized Illicit Financial Flows . . . . . . . . . . 24 Africa: Non-normalized Illicit Financial Flows Indicators, 1980-2009 . . . . . . . . . . . . . . 31
African Development Bank and Global Financial Integrity
Acronyms and Abbreviations AEI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Automatic Exchange of Information AfDB. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . African Development Bank ALSF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . African Legal Support Facility ATAF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . African Tax Administration Forum BIS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Bank for International Settlements BOP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Balance of Payments BroadNRTNon-norm. . . . . . . . . . . . . . . . . . . . . . . . . Broad Net Resource Transfers Non-normalized BroadNRTNorm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Broad Net Resource Transfers Normalized CABRI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Collaborative Africa Budget Reform Initiative CED. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Change in External Debt DAC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Development Assistance Committee DTAAs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Double Tax Avoidance Agreements EITI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Executive Industries Transparency Initiative EU. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . European Union EUSTD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . EU Savings Tax Directive FATF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Financial Action Task Force FDI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Foreign Direct Investment GER. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gross Excluding Reversals GFI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Global Financial Integrity GTSP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Global Tax Simplification Program HIPC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Heavily Indebted Poor Countries ICF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Investment Climate Facility IFC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . International Finance Corporation IFFS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Illicit Financial Flows IFF Non-normalized . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Illicit Financial Flows Non-normalized IFF Normalized . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Illicit Financial Flows Normalized MGDs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Millennium Development Goals NarrowNRTNon-norm . . . . . . . . . . . . . . . . . . . . . . Narrow Net Resource Transfers Non-normalized NarrowNRTNorm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Narrow Net Resource Transfers Normalized NDF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Net Debt Flow NRecT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Net Recorded Transfers NRT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Net Resource Transfers Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
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ODA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Official Development Assistance OECD . . . . . . . . . . . . . . . . . . . . . . . . . . . . Organization for Economic Cooperation and Development OFCS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Off-shore Financial Centers OHADA. . . . . . . . . . . . . . . . . . . . Organisation pour l’Harmonisation en Afrique du Droit des Affaires PPI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Producer Price Index RMCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Regional Member Countries SSA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sub-Saharan Africa SWFs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sovereign Wealth Funds WEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IMF World Economic Outlook
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African Development Bank and Global Financial Integrity
Executive Summary This report analyses the volume and pattern of recorded and unrecorded capital flows to and from Africa and its various regions and country groups over the period 1980-2009. It also provides the main trends of resource transfers; it does not provide an analysis of the reasons underlying the flows. Further analysis on the dynamics of the flows will need to be based on indepth, country-specific work. For the purposes of this study, recorded “capital flows” are financial and non-financial transactions recorded in the balance of payments, whereas unrecorded capital flows primarily involve the “flight” of capital. The report assumes that unrecorded capital flows are illicit in nature and involve the transfer of money earned through corruption, kickbacks, tax evasion, criminal activities, and transactions of certain contraband goods. Likewise, legal funds earned through legal business but transferred abroad in violation of exchange control regulations also become illicit. More specifically, net recorded transfers (NRecT) are based fully on recorded balance of payments items. The narrow version of this measure, NRecT Narrow, is simply equal to the Financial Account Balance, whereas the broad measure, NRecT Broad, is equal to the Financial Account Balance plus the sum of net current and net capital transfers. Net resource transfers (NRT) are calculated by the difference between NRecT and illicit financial flows (IFF), which also have two versions, normalized (conservative) and non-normalized (robust). Hence, there are four alternate measures of NRT, corresponding to the version of recorded transfers and outflows of illicit capital. These concepts are important as they enable a comparison of NRecT against unrecorded outflows of illicit capital. Results indicate that Africa was a net creditor to the world, as measured by the net resource transfers, to the tune of up to US$1.4 trillion over the period 1980-2009, adjusted for inflation. While there were brief periods in the early 1980s and the 1990s, when Africa received small net resource transfers from the rest of the world, the continent has been a net provider of resources to the world with estimates of real NRT ranging from US$597 billion to US$1.4 trillion, depending on the definition used for the transfers (NRecT, Narrow or Broad, and IFF, normalized or non-normalized). The most optimistic estimate of NRT (or lowest negative NRT of US$597 billion) involves broadly defined recorded transfers net of conservatively estimated illicit outflows (BroadNRTNorm), while the most pessimistic scenario (negative transfers amounting to US$1.4 trillion) involves narrowly defined recorded transfers net of robust estimates of illicit outflows (NarrowNRTNon-norm).
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
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If we focus on recorded transfers, that is, not taking account of illicit outflows, we find that, according to the NRecT Narrow measure, there were net inflows to Africa over the period 1980-1999 and a sharp reversal to net outflows in the period 2000-2009. The NRecT Narrow measure shows that African countries received resources amounting to 2.3 percent of GDP in the 1980s and just under 1.0 percent of GDP in the 1990s. However, the continent became a net lender of resources to the world over the decade ending 2009. This sharp reversal from net inflows over the earlier two decades to net outflows over the last decade was mainly due to outflows associated with reserve accumulation, reflecting African countries’ desire to self-insure against financial crisis. The recorded outflows from Africa in the past decade were not evenly distributed across regions. They were largely driven by outflows from North Africa. Considering the period 2000-2009 alone, some US$30.4 billion per annum flowed out of Africa with 83 percent of such outflows originating from North Africa. Within Sub-Saharan Africa, the results from the NRecT Narrow measure were mixed. West and Central Africa experienced considerable outflows, which swamped resource transfers into other regions over the decade ending 2009. NRecT Narrow losses from the West and Central regions were mainly driven by outflows related to repayment of loans and trade credits, rather than reserve accumulation. The distribution of gains and losses of transfers among African countries was asymmetrical, resulting in a net loss of transfers from Africa. The top five countries that gained transfers (NRecT Narrow) over the period 1980-2009 are South Africa, Sudan, Tunisia, Morocco, and Cote d’Ivoire, while Algeria, Libya, Nigeria, Botswana, and Egypt lost such transfers. The volume of transfers lost from the latter five countries far outstripped those gained by the former five. The broader measure of recorded transfers (NRecT Broad) alters the long-run developments in net recorded transfers owing to the impact of current and capital transfers (which principally include remittances and debt relief). Based on the broad measure, Africa’s transfers (NRecT Broad) increased from an average inflow of about US$27 billion per annum in the 1980s and 1990s before declining to US$8.7 billion in the last decade ending 2009. The broad measure does not show that Africa swung from net debtor to net creditor to the world in the 2000s mainly due to substantial current and capital transfers such as remittances, migrant transfers, debt forgiveness and write-offs, and other non-financial transfers which provided off-setting effects. Every region of Sub-Saharan Africa received resources on a net basis throughout the three decades, based on the broad measure of transfers, with the largest gains going to the West and Central Africa region. West and Central Africa received the most resources over the 30-year period, in terms of GDP, increasing from 5.2 percent of GDP per annum in the 1980s to 5.7 percent in the 1990s, before declining to 2.3 percent in the last decade. Recorded transfers were mainly driven by remittances and debt forgiveness, rather than net foreign direct investments.
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African Development Bank and Global Financial Integrity
Country resource endowment matters when transfers are measured on a broad basis. For instance, non-fuel exporters came out ahead of fuel-exporters in attracting net recorded transfers measured on a broad basis. Debt-relief also helped low-income countries to recapture some of the resources. Heavily Indebted Poor Countries (HIPC) experienced a modest increase in transfers over the three decades. On an average per annum inflation-adjusted basis, resource inflows to HIPC countries increased from US$14.0 billion in the 1980s to US$14.3 billion in the 1990s, before jumping to US$20.8 billion over the last decade ending 2009. North African countries dominated the top gainers over the 30-year period, based on broad categorization of net recorded transfers. Egypt, Morocco, Tunisia, Kenya, and Ghana were the top five gainers of broad-based recorded resource transfers over the 30-year period 1980-2009; Libya, Algeria, Gabon, Botswana, and Angola were the top five losers of recorded transfers. Illicit financial flows (IFFs) were the main driving force behind the net drain of resources from Africa of US$1.2 - 1.3 trillion on an inflation-adjusted basis. IFFs grew at a much faster pace over the 30-year period 1980-2009 than net recorded transfers, even accounting for the net inflows arising from the broad net recorded transfers. Illicit outflows were dominated by outflows from Sub-Saharan Africa, especially from West and Central Africa. Illicit outflows from Sub-Saharan Africa outstripped those from North Africa by over two times in nominal terms while in real terms, three African regions—West and Central Africa at US$494.0 billion (37 percent), North Africa at US$415.6 billion (31 percent), and Southern Africa at US$370.0 billion (27 percent)—account for 95 percent of total cumulative illicit outflows from Africa over the 30-year period. (See Chart 4 and Table 1). In terms of the volume of illicit financial flows, Nigeria, Egypt, and South Africa led the regional outflows. In West and Central Africa, outflows were largely driven by Nigeria, the Republic of Congo, and Cote d’Ivoire in that order of magnitude while North Africa outflows were dominated by Egypt, Algeria, and Libya respectively. Outflows from Southern Africa were mainly driven by South Africa, Mauritius, and Angola. The study concludes by offering policy recommendations with respect to (i) initiatives to restrict the absorption of illicit financial flows, (ii) policies to curtail illicit financial outflows from Africa, and (iii) policies to boost net recorded transfers by improving the business climate. To ensure greater effectiveness, it is imperative that there is policy alignment between African countries and “absorbing” countries in addressing the issue of illicit financial flows. With regard to stemming the absorption of illicit financial flows, the following policy initiatives could be considered: • Promoting transparency in the financial system: Banks and offshore financial centers (OFCs) should be required to regularly report to the Bank for International Settlements (BIS) detailed deposit data by sector, maturity, and country of residence of deposit holders. Moreover, the BIS
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
3
must be permitted to publicly disseminate the cross-border banking data for specific source and destination countries. Further, the obscurity of information on the beneficial ownership of companies, trusts, and other legal entities must be addressed. Domestic laws governing financial institutions should be strengthened to make it illegal to open accounts without knowledge of the natural person(s) owning the accounts (i.e., its beneficial owners). • Entering into automatic exchange of tax information agreements: Tax evasion is at the heart of the world’s shadow financial system and constitutes a significant component of illicit financial flows. One way to address the problem of tax evasion is for African countries to enter into automatic exchange of information (AEI) agreements with the destination countries where the proceeds of tax evasion are lodged. AEI agreements should be accompanied by double tax avoidance agreements, which set clear rules for countries’ ability to assess taxes and monitor compliance according to international norms, making it more difficult for individuals and entities to shift income between countries. With respect to policies aimed at curtailing illicit financial outflows from Africa, policy initiatives are geared to resource-rich and resource-poor countries and include the following: • In resource-rich countries, the natural resource sector is usually the main source of illicit financial flows. These countries generally lack the good governance structures that would enable citizens to monitor the amount and use of revenues from the natural resource sector. These countries should promote transparency and accountability through the strengthening of civil society organizations and the implementation of open and transparent budgeting processes such as the Open Budget Initiative, the Collaborative Africa Budget Reform Initiative (CABRI), and the Extractive Industries Transparency Initiative (EITI). Countries will also need to look beyond the EITI to ensure that policies are in place to facilitate greater transparency and accountability over the entire resource value chain. Further, multinational companies operating in African countries should be required to publish annual financial reports that explicitly include their activities in Africa. • In resource-poor countries, illicit financial flows largely arise from the mispricing of trade by companies of all sizes. This activity is a form of money laundering and tax evasion. These countries should focus on strengthening legal institutions and anti-corruption laws and empowering regulatory agencies to exercise adequate oversight. Specifically: • Undertaking tax reform to widen the tax base. Tax reform applicable to a broad group of taxpayers is not only fair but will ensure greater tax compliance than a proliferation of indirect taxes that are unwieldy to manage, costly to administer, and have large built-in incentives for evasion. • Creating a national authority for the regulation and management of public procurement to ensure greater transparency and accountability in the contracting process. The procedures and rules for bidding on government contracts should be transparent, as should be information regarding the contracts awarded. African countries should follow international best practices in the area of government contracting so as to maximize public benefit. 4
African Development Bank and Global Financial Integrity
• Reforming customs service procedures to curtail trade mispricing. This involves the removal of ad hoc exemptions from customs duties, streamlining clearance and document control procedures, and efficient computerization of payment and collection procedures in order to make procedures less cumbersome and more efficient. Additionally, capacity-building and training are needed to detect and investigate under- and over-invoicing of goods entering and leaving the country. • Strengthening anti-money-laundering initiatives and enforcement. During the last decade, many African countries have set up anti-money-laundering programs under which financial institutions are required to report suspicious transactions to the relevant authorities. However, there is a need to strengthen the capacity of the relevant authorities to initiate appropriate legal actions on the basis of these reports. Policies to boost net recorded transfers by improving the business climate generally involve measures that range from improving a country’s political and economic stability to specific business-friendly measures to improve infrastructure, rationalize corporate taxation, and strengthen governance.
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I
I. Introduction Recently, the analysis of capital flows to and from Africa has received growing attention (Kar and Cartwright-Smith (2010) and Ndikumana and Boyce (2008)). Indeed, Ndikumana and Boyce (2008) argue that the problem of capital flight from Africa deserves special attention on four accounts. First, capital flight constitutes a diversion of scarce resources away from the domestic economy and other productive activities as evidenced by the significantly lower investment levels in African countries compared to other developing countries. Second, capital flight is likely to have pronounced detrimental effects on the distribution of wealth, thereby undermining growth and exacerbating income inequality. Third, Sub-Saharan African countries still receive significant amounts of external loans. Fourth, in several country case studies involving India, Mexico, and Russia, Kar (2010), and Kar and Freitas (2011 and 2012), find strong evidence that illicit financial flows both drive and are driven by underground economic activities. Previous African Development Bank (AfDB or Bank) work in this area has fallen under the broader domain of transparency and governance. Consequently, the Bank’s Governance Department focuses on strengthening transparency and accountability in the management of public resources and enhancing the business enabling environment. Indeed, governance is identified as a key priority in the Bank’s Medium Term Strategy, with 23 operations totaling UA 377 million (about US$579 million) programmed for delivery in 2012. The Bank has continued to focus its support towards economic and financial governance. It operates as a significant partner in joint donor support arrangements and has developed a stronger organizational capacity and structure for the design, appraisal, management, and monitoring of program based operations. Further, in the governance area, the Bank is leading the development of the African Governance Outlook, which will provide data and analysis on financial governance performance and trends so as to inform the Bank’s strategies and operations, resulting in effective action towards the core governance issues of a specific country or region. In addition, the Bank remains supportive of regional initiatives, networks and programs that promote and harmonize standards and codes of good economic and financial governance including enhancing the regulatory framework Organisation pour l’Harmonisation en Afrique du Droit des Affaires (OHADA), improving the Investment Climate Facility (ICF), and transparency in the extractive industries Executive Industries Transparency Initiative (EITI).
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In fact, EITI implementation in Regional Member Countries (RMCs) has gained momentum and the Bank is increasing its support in improving governance of the extractive sector for the entire value chain. Twenty-one RMCs are currently implementing the EITI standard in Africa, of which seven have reached compliance status. All twenty-one EITI implementing countries have established a multi-stakeholder group with a broad range of representatives to foster transparency and accountability in the extractive industry. Also, renewed effort has been given to outreach activities targeting middle-income countries and new resource rich countries to make credible commitments to good governance of natural resources. The Bank is also increasing its support to demand-side governance to strengthen the capacities of civil society to play a more active role in holding governments accountable. The Bank also supports the work of the African Legal Support Facility (ALSF) on vulture funds. In general, this facility builds capacity in African countries to reinforce their ability to negotiate complex contracts so as to achieve an optimal solution. Related to illicit financial flows, some work is underway on the recovery of stolen assets in African countries. On the specific area of capital flows, recent work (Kar and Cartwright-Smith (2010)) that focused on illicit financial flows out of Africa over the period 1970 to 2008 estimated these flows conservatively at US$854 billion with the upper bound as high as US$1.8 billion and the bulk of financial outflows from West and Central Africa. These outflows from Africa significantly outpaced official development assistance and were persistent over this period, growing at 12.1 percent per annum. The present work examines the volume and pattern of recorded and unrecorded capital flows to and from Africa and its various regions and groups over the period 1980 – 2009. Recorded “capital flows” refer to financial and non-financial transactions that are recorded in the balance of payments whereas unrecorded capital flows primarily involve the flight of capital and are assumed to be illicit in nature. Accordingly, net resource transfers (NRT) is defined as recorded transactions in the balance of payments minus illicit financial flows. This work builds on previous work in this area in three important ways. First, it broadens previous Bank work in this area beyond transparency and governance to include work on capital flows to and from Africa. Second, while the previous report on Africa focused only on illegal capital flight or illicit financial flows, this work is broader as it presents both alternative estimates of net resource transfers (NRT) based on narrow and broad measures of net recorded transfers and nets out illicit financial flows. While several definitions of NRT exist in the literature (Didszun (1990) and Osterkamp (1990)), the United Nations definition of NRT as total receipts of financial and other resource inflows from abroad plus foreign investment income minus total resource outflows including increases in foreign 8
African Development Bank and Global Financial Integrity
reserves and foreign investment payments more closely corresponds to the definition of NRecT Broad used in this study. Third, unlike the previous work on Africa, this work presents two methods of estimating illicit financial flows namely, (i) Normalized or conservative method of considering gross outflows and, (ii) Non-normalized or robust method of estimating gross outflows. The analysis is largely based on gross outflows, as we argue that unrecorded inflows cannot be factored into any planning by government by virtue of their unrecorded nature. This study does not seek to explain the relationship between NRT and the performance of African economies. Nor does it examine the impact of net transfers on social expenditures or the attainment of the Millennium Development Goals (MDGs). Rather, the objective of the study is to present alternative estimates of NRT and to analyze their long-term evolution for African countries and regions. This is no less a daunting task given the extensive data gaps on African countries and the lack of a consensus on how NRT should be estimated. Further, the work also provides a discussion on policies to curtail these flows. The findings in this study are only indicative and provide a basis for further detailed country work. The paper is organized as follows: Section II presents the methodological approach of this work before Section III discusses Net Recorded Transfers. Section IV considers Illicit Financial Flows while section V presents the results on the Net Resource Transfers. Policy recommendations are offered in Section IV before conclusions are drawn in Section II.
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II. Methodological Approach
II
i. Key Definitions and Terminology1 Boxes 1 and 2 below provide the definitions for the key terms used in the paper.
Box 1: Defining Net Recorded Transfers (NRecT) and Net Resource Transfers (NRT) Net recorded transfers (NRecT) capture a country’s net capital inflows and outflows as recorded in its balance of payments. Net resource transfers (NRT) are obtained by netting out illicit financial flows from NRecT. These two concepts are important because they facilitate the comparison between net recorded transfers and unrecorded outward illicit financial flows (IFF). There are two measures of NRecT, Narrow and Broad. NRecT Narrow =
Financial Account Balance
NRecT Broad
NRecT Narrow + Net Current Transfers + Net Capital Transfers
=
There are also two measures of illicit flows—normalized (conservative) and non-normalized (robust). Hence, there are four alternative ways to estimate net resource transfers (NRT): NarrowNRTNon-norm =
NRecT Narrow – IFF Non-normalized
NarrowNRTNorm
=
NRecT Narrow – IFF Normalized
Broad NRTNon-norm
=
NRecT Broad – IFF Non-normalized
BroadNRTNorm
=
NRecT Broad – IFF Normalized
Source: Global Financial Integrity (GFI)
Box 2: Normalization of Illicit Financial Flows (IFF) estimates IFF Estimates are either “normalized,”/conservative or “non-normalized”/robust. Normalized IFFs satisfy two conditions: (i) capital outflows must be seen in the majority of the years covering a time period, and, (ii) capital outflows must exceed a minimum of 10 percent of the country’s exports, the assumption being that lower levels may be due to data problems rather than genuine illicit financial flows. Non-normalized IFFs includes all estimates of illicit financial flows no matter how small. Even if there are illicit outflows from a country in one year within a sample period, that country’s capital outflows are included in regional totals. Given the nature of this study, we impose the second condition only in the normalized estimates of illicit flows generated in this report Source: Global Financial Integrity (GFI) Appendix presents a detailed discussion of the key balance of payments concepts with an illustrative example of the Ghana financial account.
1
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ii. Overall Approach The overall methodological approach is built on the balance of payments system. The current account balance is defined as the difference between capital flight and net recorded transfers (Osterkamp, 1990). Inflows and outflows of financial and non-financial transfers as recorded in the Balance of Payments (BOP) (also known as net recorded transfers, or NRecT) net of illicit financial flows yield net resource transfers (NRT). CA Balance = К – NRecT
Accordingly, when capital flight exceeds (falls short of) net recorded transfers, we have a current account surplus (deficit). A current account surplus implies a net transfer of resources to the world, while a current account deficit implies a net absorption of resources from the world. However, the above link between the current account balance, capital flight, and net recorded transfers is incomplete due to three reasons. First, the above equation includes capital flight derived directly from balance of payments components (comprising the World Bank Residual method). Hence, the equation assumes away trade misinvoicing which is considerable for most developing countries. Second, the above equation would hold more for the narrow version of recorded transfers than the broad measure, which includes debt forgiveness, remittances, workers’ transfers, and other items. Third, the change in external debt in most cases is not equal to the flows recorded in the balance of payments, and the discrepancies between the change in stock and the corresponding flows in the BOP will introduce discrepancies. Indeed, reliance on the current account to indicate the scale of net resource transfers to a country cannot provide policy guidance because, for that perspective, we need to estimate the scale of both recorded and unrecorded or illicit financial flows. In short, a double-prong strategy to increase recorded inflows and curtail unrecorded or illicit outflows needs to be developed in order to boost net resource transfers into the country. As noted, net resource transfers (narrow or broad measure) are estimated in three steps: namely, first, determine total financial and non-financial transfers to and from a country as recorded in its balance of payments; second, estimate illicit financial flows due to unrecorded leakages from the balance of payments, adjusting these flows for trade misinvoicing; and third, net out the recorded and unrecorded capital flows. For the first step, net recorded transfers are estimated based either on the Narrow measure (NRecT Narrow, which is the financial account balance) or the Broad measure (NRecT Broad) which equals NRectT Narrow plus net current transfers and net capital transfers.2 The second step involves the estimation of illicit financial flows using the World Bank Residual measure adjusted for trade misinvoicing. This can be done in one of three ways, namely, (i) the “Traditional” method, whereby illicit inflows are netted out from illicit outflows, (ii) the Normalized method, by which only large 12
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outflows (exceeding at least 10 percent of exports) are included, and (iii) the Non-normalized method, which includes all outflows without regard to magnitude3 (reference Box 2). While all possible permutations and combinations of the two estimates of NRecT (Narrow and Broad) and three methods of estimating IFFs (Traditional, Normalized, and Non-normalized) result in six alternative estimates of NRT, we do not include NRT estimates based on the Traditional method of calculating IFFs. The reasons for excluding the Traditional IFF estimates are discussed in Illicit Financial Flows from Developing Countries: 2002-2006, published by Global Financial Integrity in 2008). The four remaining indicators span a range of NRTs based on how we view recorded and unrecorded transfers from Africa and its various regions and country groupings (reference Box 1).
a. Data Issues for Africa We discuss two aspects of related to data issues: (i) choice of time period, and (ii) missing data. 1.
Choice of Time Period
The choice of the time period for the report (1980-2009) is dictated by the period for which relevant balance of payments data are available for the largest number of African countries (see Appendix Chart A1 and Table A2). Specifically, the availability on information on the financial account, which is the narrow measure of NRecT, is the binding constraint, as Broad NRecT cannot be computed without it. The data gap analysis shows that 24 countries in Africa (23 in sub-Saharan Africa and one in North Africa) have considerable data gaps. 2.
Strategy for Dealing with Missing Data
There are three approaches in dealing with missing data. First, simply dropping the countries with the missing data from all calculations of NRecT, illicit flows, and net recorded transfers, NRT would considerably distort and understate the flows to and from Africa (as eliminating 24 out of 53 African countries will have a significant impact on flows in both directions). Moreover, the dropped countries will distort the regional breakdown and pattern of distribution in NRecT, illicit flows, and NRT. Second, estimating the missing data by interpolation may result in recorded transfers that are not realistic for countries in civil and political turmoil. Third, assuming that both NRecT Narrow and Broad are equal to the opposite of the net of current account balance (on which estimates can be Recall, the Broad measure expands the Narrow one by including, for example, debt forgiveness, worker’s remittances, migrant transfers, and certain types of charities and donations in cash or kind that are not included in the financial account balance. Note that it is possible for NRecT Narrow and NRecT Broad to have opposite signs; for instance, NRecT Narrow can show net outward transfers while NRecT Broad can show net inward transfers or vice-versa. Of course, for countries that have received substantial transfers through debt forgiveness and write-offs or those that have received significant worker remittances, an estimation of NRT based on NRecT Broad is more relevant than one based on NRecT Narrow.
2
The normalized method imposes a size filter to reduce the risk of including estimates that are generated by statistical errors in trade and balance of payment series. The size of the 10 percent filter should be viewed in relation to the IMF’s finding that the goods trade discrepancy (i.e., exports minus imports), which should be zero at the global level, amounts to an average of about 1 percent of world exports over the period 2002-2007. Hence, we can safely say that discrepancies larger than the 10 percent of exports threshold are unlikely to be due to statistical errors in recording.
3
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obtained from the IMF’s World Economic Outlook exercise). However, NRT will be understated to the extent that estimates for trade misinvoicing cannot be calculated or that they are understated. We employ the third strategy.
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III. Net Recorded Transfers
III
This section considers the evolution and patterns of net recorded transfers, illicit financial flows, and net resource transfers over the period 1980-2009 and how these flows are distributed across African regions and groups of countries. We begin with a discussion of net recorded transfers (both narrow and broad, with a focus on the latter) and consider : (i) the evolution and pattern of distribution of NRecT Narrow and NRecT Broad for Africa, its regions, and the countries that drive them, (ii) the relationship between the two measures of recorded transfers, (iii) how these measures evolve in real terms and in terms of GDP, (iv) shifts in the composition of net recorded transfers, and (v) the main countries that have gained and lost recorded flows over the thirty-year period. In order to carry out the above analysis for the period in question, we assume that for countries with missing data or data gaps, i.e., those countries which stopped reporting data for the period in turmoil due to civil war (e.g., Liberia, Sierra Leone, Somalia) or severe economic crisis (e.g., Zimbabwe), NRecT Narrow (or Broad) is approximated by the countries’ current account position. This assumption implies that, for all intents and purposes, current transfers and capital transfers are zero so that NRecT Narrow and NRecT Broad are equal. In other words, these countries do not receive debt forgiveness and write-offs or worker remittances for the period in question. While this assumption may have its shortcomings, it is preferable to dropping the countries with missing data from the regions and the groups which would bias the regional and group totals. Moreover, as countries that are in severe social and economic turmoil are unlikely to receive debt forgiveness and write-offs or significant remittances, the assumption that net current and capital transfers are zero is not unrealistic.
i. Narrow Measure In real terms, the financial account or NRecT Narrow measure declined from an average annual inflow of US$9.6 billion for Africa as a whole in the 1980s (or 2.3 percent of GDP) down to US$4.6
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billion in the 1990s (or 1 percent of GDP). In the last decade (up to 2009), it is estimated that about US$30.4 billion per annum (or 3.2 percent of GDP) flowed out of Africa in net recorded transfers (as measured by NRecT Narrow). About 80 percent of these outflows, or US$25.2 billion, was out of North Africa. The sharp reversal of average annual net recorded inflows in the 1980s and 1990s to net annual recorded outflows over the last decade was mainly due to an increase in outflows associated with reserve accumulation (possibly in relation to African countries’ greater desire to self-insure against financial crisis), and, to a lesser extent, outflows associated with other investments. North Africa demonstrates a faster pace of reserve accumulation, mainly driven by oil exports, relative to the pace in Sub-Saharan Africa. Indeed, this last period coincided with the period of high oil prices, during which the oil-rich North African countries (such as Libya) benefited. In general, high oil prices translate to higher reserves. Given that an increase in reserves is entered into the balance of payments with a negative sign, which is consistent with the investment of those reserves abroad, the increase in financial outflows during the 2000s does not come as a surprise. In fact, our analysis on fuel exporters supports this, showing that fuel exporters collectively attracted net recorded transfers of US$4.2 billion per annum in the 1980s, registered small net outflows of US$0.6 billion per annum in the 1990s, and experienced net outflows of US$38.6 billion in the last decade. Based on NRecT Narrow, all regions within Sub-Saharan Africa (SSA), including Horn of Africa, Great Lakes, and Southern Africa, consistently attracted net recorded transfers, that is, experienced net recorded inflows, throughout the three decades. However, West and Central Africa registered net recorded outflows of US$9.7 billion per annum in the last decade. This loss offset recorded inflows into the three other regions (Horn of Africa, Great Lakes, and Southern Africa) resulting in net outflows from SSA in the last decade. Net recorded transfers from West and Central Africa were mainly driven by net outflows of other investments (involving repayments of loans and trade credits) rather than reserve accumulation. Considering individual African countries, the distribution of net recorded transfers was asymmetrical. Chart 1 shows that in descending order of magnitude, the top five gainers (measured by NRecT Narrow, deflated by the U.S. Producer Price Index (PPI) over the period 1980-2009 are South Africa, Sudan, Tunisia, Morocco, and Cote d’Ivoire, while the top five losers of NRecT Narrow were Algeria, Libya, Nigeria, Botswana, and Egypt which are all resource-rich countries. However, total net recorded transfers lost by the top five countries outstripped the resource gains of the top five by three to one, resulting in net outflows for Africa. Further work is needed to better understand the driving forces of these flows at country level.
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Chart 1. Top Five Gainers and Losers of Real Net Recorded Transfers Narrow, Chart 1. Top Five Gainers and Losers of Real Net Recorded Transfers Cumulative 1980-2009 Narrow, CumulaAve 1980-‐2009 (in millions of 2005 U.S. dollars) deflated with CPI, base 2005
-‐140,000 -‐120,000 -‐100,000
-‐80,000
Millions of U.S. dollars -‐60,000 -‐40,000 -‐20,000
Algeria
0
20,000
40,000 South Africa
Libya
Sudan
Nigeria
Tunisia
Botswana
Morocco
Egypt
Cote d'Ivoire
Note: Deflated with PPI, base 2005 Source: GFI and AfDB Staff Estimates
i. Broad Measure We now turn to the broad measure, which, in addition to the financial account balance, includes net current transfers (e.g., workers’ remittances) and net capital transfers (e.g., debt forgiveness and write-offs) and is therefore more representative of the African flows given the prominence of remittances and debt forgiveness in African economies. The long-run developments in net recorded transfers look markedly different if we use the broad measure. In the 1980s and 1990s, Africa attracted considerably higher inflows, averaging US$27 billion per annum or 4.3 percent of GDP. Over the last period (2000-2009), Africa continued to attract net recorded transfers from the world, albeit at the much slower pace of US$8.7 billion per annum. The broad measure does not show the swing from net debtor to net creditor in the 2000s because of substantial net positive current transfers such as remittances. In comparison, debt forgiveness played a comparatively minor role in keeping net recorded transfers in positive territory on account of their size in relation to remittances. But net recorded transfers broadly defined (NRecT Broad) behaved differently in the two main regions of Africa-in Sub-Saharan Africa, they remained strongly positive throughout the three decades, while in North Africa, net inward transfers declined progressively from 3.8 percent of GDP in the 1980s to 2.1 percent of GDP in the 1990s changing to 2.1 percent in net outward transfers per year from the region as a whole over the last decade. So, unlike Sub-Saharan Africa, in North Africa, both the Narrow and Broad measures of recorded transfers turned sharply negative over the last decade. This result needs to be investigated further, as it would suggest a comparatively limited role of remittances in the North African economies.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
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According to the broad measure of NRecT, every region of Sub-Saharan Africa received resources on a net basis throughout the three decades. Resource inflows into all four regions increased steadily from the 1980s to the 1990s with the exception of West and Central Africa. Over the last decade, recorded inflows per annum (broadly measured) increased further in the case of the Horn of Africa, the Great Lakes, and the West and Central Africa regions but fell slightly in the case of Southern Africa. In terms of regional GDPs, the Horn of Africa received the most recorded transfers over the 30year period, increasing from 5.4 percent in the 1980s to 8.6 percent in the 1990s and further to 13.4 percent in the last decade. Significant net current transfers driven mainly by workers’ remittances were responsible for boosting recorded transfers into the Horn of Africa and the Great Lakes regions. By and large, net FDI inflows played a smaller role in driving such transfers into any region, although they became more important over the last decade. The group of non-fuel exporters came out ahead of fuel exporters in attracting net recorded transfers (Broad) throughout the past 30 years. Net transfers increased from around US$4.8 billion per annum in the 1980s and 1990s to US$5.4 billion in the decade ending 2009. In comparison, net recorded transfers into fuel exporters declined from US$3.1 billion per year on average in the 1980s to US$1.5 billion in the 1990s, before they collectively became a net creditor to the world with outflows of about US$27 billion per annum in the last period. The reversal of net recorded transfers from fuel exporters mainly came about due to outflows associated with reserve accumulation as a result of oil exports. In addition, fuel exporters made significant repayments of loans during this period. On a positive note, net resource transfers into the group of heavily indebted poor countries, broadly measured in inflation adjusted terms, increased throughout the three decades from US$14.0 billion in the 1980s to US$14.3 billion in the 1990s, picking up further to US$20.8 billion over the last decade. Considering the individual countries, Chart 2 shows that, based on the broad measure, the top gainers in descending order of magnitude and in real terms were Egypt, Morocco, Tunisia, Kenya, and Ghana, while the top five losers were Libya, Algeria, Gabon, Botswana, and Angola.
Chart 2. Top Five Gainers and Losers of Real Net Recorded Transfers Broad, Chart 2. Top Five Gainers and Losers of Real Net Recorded Transfers Cumulative 1980-2009 Broad, CumulaAve 1980-‐2009 (in millions of 2005 U.S. dollars) deflated with CPI, base 2005
-‐165,000
-‐115,000
-‐65,000
Libya
85,000
135,000
185,000 Egypt
Algeria
Morocco
Gabon
Tunisia
Botswana
Kenya
Angola
Ghana
Note: Deflated with PPI, base 2005 Source: GFI and AfDB Staff Estimates
18
Millions of U.S. dollars -‐15,000 35,000
African Development Bank and Global Financial Integrity
We note that regardless of the measure used (broad or narrow), the main gainers of net recorded transfers are Tunisia and Morocco while the main losers are Algeria, Libya, and Botswana.
Summary • The narrow version of net recorded transfers (NRecT Narrow) shows that over the last decade ending 2009, US$30.5 billion per annum flowed out of Africa; some 81 percent of such outflows were from North Africa. There was a sharp reversal from net inflows over the earlier two decades to net outflows over the last decade, mainly due to outflows associated with reserve accumulation reflecting African countries’ desire to self-insure against financial crisis. • Within Sub-Saharan Africa, narrowly defined net recorded outflows from West and Central Africa swamped recorded transfers into other regions over the decade ending 2009. NRecT Narrow losses from that region were mainly driven by outflows related to repayment of loans and trade credits rather than reserve accumulation. • According to the NRecT Narrow measure, African countries received inflows amounting to 2.3 percent of GDP in the 1980s and just under 1.0 percent of GDP in the 1990s. However, the continent became a net lender of resources to the world (amounting to some 3.2 percent of GDP) over the decade ending 2009. • Net FDI flows into the Sub-Saharan African region accelerated even faster than those into North Africa. Starting at about 0.5 percent of GDP on average in the 1980s, they more than doubled to 1.2 percent of GDP in the 1990s. Over the last decade, net FDI inflows into the region nearly tripled to 3.5 percent of GDP. • The distribution of NRecT Narrow among African countries is asymmetrical. The top five countries that gained NRecT Narrow over the period 1980-2009 are South Africa, Sudan, Tunisia, Morocco, and Cote d’Ivoire, while Algeria, Libya, Nigeria, Botswana, and Egypt lost such transfers. The volume of transfers lost from the top five countries far outstripped those gained by the top five. • Long-run developments in net recorded transfers look quite different if we use the broader measure of transfers. Africa’s NRecT Broad decreased from an average inflow of about US$27 billion per annum in the 1980s and 1990s before declining to US$8.7 billion in the last decade ending 2009. The broad measure does not show that Africa swung from net debtor to net creditor to the world in the 2000s mainly due to substantial current and capital transfers such as remittances, migrant transfers, debt forgiveness and write-offs, and other non-financial transfers. • According to the broad measure of transfers, every region of Sub-Saharan Africa received resources on a net basis throughout the three decades covered by this study. In terms of GDP, the Horn of Africa received the most resources over the 30-year period, increasing from 5.4 percent of GDP per annum in the 1980s to 8.6 percent in the 1990s and further to 13.4 percent in the last decade. Recorded transfers were mainly driven by remittances and debt forgiveness than by net foreign direct investments. • Non-fuel exporters came out ahead of fuel-exporters in attracting net recorded transfers
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
19
measured on a broad basis. Recorded inflows into the group of heavily indebted poor countries in Africa continued to increase modestly throughout the three decades. On an average per annum basis, they increased from US$14.0 billion in the 1980s, to US$14.3 billion in the 1990s, before jumping to US$20.8 billion over the last decade ending 2009. • Egypt, Morocco, Tunisia, Kenya, and Ghana were the top five gainers of broad-based recorded resource transfers over the 30-year period 1980-2009, whereas Libya, Algeria, Gabon, Botswana, and Angola were the top five losers of recorded transfers. These rankings are based on NRecT Broad in real (or inflation-adjusted) terms.
20
African Development Bank and Global Financial Integrity
IV. Illicit Financial Flows
IV
Broadly speaking, illicit financial flows involve the transfer of money earned through corruption, kickbacks, tax evasion, criminal activities, and transactions involving certain contraband goods. Likewise, funds earned through legal business activity but transferred abroad in violation of exchange control regulations also become illicit. The concept of illicit financial flows differs from the concept of capital flight, which broadly captures outflows of resident capital in response to the distortionary impact of domestic policies and political instability. In other words, the term “capital flight” largely puts the emphasis on the “push” factors in developing countries. Illicit financial flows consider both the push factors in developing countries as well as the “pull” factors in developed countries. Two channels have been identified through which illicit financial flows, unrecorded in official statistics, can flow out of a country: • External accounts, whereby illicit financial flows are captured by the Change in External Debt (CED) measure, and • Mispricing of external transactions, whereby illicit financial flows are captured by the Gross Excluding Reversals (GER) measure.
i. Methods of Estimating Illicit Financial Flows Therefore, illicit financial flows from a specific country are estimated through the CED version of the World Bank Residual method adjusted for trade mispricing (using the GER method) in their normalized and non-normalized forms. The World Bank Residual method has obvious limitations as it cannot capture swap, arrangements such as the “hawala system”, cross border smuggling of goods, criminal activities, assets swaps, and faked transactions, as they are impossible to be traced using official statistics. With regard to capital flight, several researchers such as Ajayi (1997), Collier et al (2001), and Ndikumana and Boyce (2008), have analyzed this problem in Sub-Saharan Africa. However, there have been comparatively fewer studies on this subject for North African countries, with the exception of the recent work by Ndikumana and Boyce (2012), which shows these flows to be considerable at US$459 billion (in constant 2010 dollars).
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
21
Box 3: The World Bank Residual Method (Change in External Debt (CED)) The World Bank Residual method is one of the most popular methods to estimate unrecorded flows of capital due to its ease of use. It is defined as the difference between a country’s source of funds and the recorded use of these funds. Source of funds comprises the change in the public sector’s gross external indebtedness (an approximation of net debt flow) to which is added the net flow of foreign direct investment. Use of funds includes the current account balance and the change in central bank net reserves. A rigorous estimate of this method takes into account debt forgiveness, exchange rate fluctuations, inflation variability, and the existence of a sovereign wealth fund. The World Bank Residual estimates can take mainly two forms: the first based on the Change in External Debt (CED), and the second based on the Net Debt Flow (NDF), which uses instead the flow of new loans rather than deriving the flows by taking the change in the stock of debt. This report utilizes the CED, which examines only the case in which source of funds is greater than use of funds, indicating illicit outflows from the Balance of Payments. We use the CED, rather than NDF, method because a much larger number of countries compile data on gross outstanding external debt than the flows of new loans. Source: Global Financial Integrity
In spite of the immense developmental needs, as Ndikumana and Boyce (2008) note, massive capital flight from the region has actually turned Sub-Saharan Africa into a “net creditor” to the rest of the world. Ajayi (1997) found that capital flight from Sub-Saharan African countries increased along with an increase in their external debt burden and management issues. Similar to Ndikumana and Boyce, Ajayi also adjusts the World Bank Residual method estimates for capital flight due to trade misinvoicing. It is worth mentioning that the methodology used by GFI to estimate illicit flows captures only gross outflows. In other words, illicit inflows, are not netted out from illicit outflows because illicit financial inflows, being also unrecorded, are neither taxable nor easily investable and therefore cannot be used for economic development.
Box 4: Trade Mispricing (Gross Excluding Reversals (GER)) Trade mispricing refers to the misinvoicing of international trade transactions with the ultimate purpose of diverting financial resources. Trade mispricing outflows have two components: export underinvoicing and import overinvoicing. In the first component, exporters understate their export revenues on their invoices and request their trading partners to deposit the balance in a foreign account. In the second component, importers overstate import expenditures, overpaying foreign exporters and asking them to divert the excess funds to a tax haven or a bank in an advanced country. Trade mispricing is estimated by the Gross Excluding Reversals (GER) method, and it incorporates these two components after adjusting for insurance and freight. Illicit inflows from trade mispricing, namely export over-invoicing and import underinvoicing, are not netted out of illicit outflow estimates in the GER method. Source: Global Financial Integrity
22
African Development Bank and Global Financial Integrity
ii. Trends in Illicit Financial Flows Tables 1 and 2 below show that, in real terms, Africa lost between US$1.2-1.4 trillion dollars over the period 1980-2009 through illicit financial flows, as captured by the conservative (or normalized) and robust (or non-normalized) estimation methods respectively. Even though these estimates are considerable, they are still likely to be understated due to missing data and the inability of economic models to capture all types of illicit flows (such as arising from drug trafficking or smuggling). Accordingly, to avoid any further underestimation of the illicit financial flows, we analyze the pattern of illicit outflows from African countries based on real non-normalized estimates of illicit financial flows. Chart 3 below shows the evolution of both estimates.
Chart 3. Africa: Real Illicit Financial Flows, 1980-2009 of U.S. dollars) (in millions Chart 3. Africa: Real Illicit Financial Flows, 1980-‐2009 (in millions of U.S. dollars deflated with CPI, base 2005)
100,000 80,000 60,000 40,000
Real IFF Non-‐normalized
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
0
1981
20,000 1980
Millions of U.S.dollars
120,000
Real IFF Normalized
Note: Deflated with PPI, base 2005 Source: GFI and AfDB Staff Estimates
Accordingly, real non-normalized illicit outflows from Africa increased from US$42.9 billion in 1980 to peak at US$103.7 billion in 2007 before slipping to US$97.5 billion in 2008 and US$74.2 billion in 2009, largely due to the global financial crisis. Economic crises typically reduce illicit flows as sources of funds decline relative to uses or if the use increases relative to the source of funds (such as higher current account deficits financed largely through a drawdown in reserves). Moreover, a fall in trade volumes as a result of the global economic crisis may also reduce the opportunities to misinvoice trade which in turn would reduce illicit outflows through this channel.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
23
Table 1. Africa: Decennial Developments in Real Non-normalized Illicit Financial Flows (in millions of 2005 U.S. dollars or in percent)
Table 2. Africa: Decennial Developments in Real Normalized Illicit Financial Flows (in millions of 2005 U.S. dollars or in percent)
Cumulative Non-normalized IFFs
Cumulative Normalized IFFs
Region
1980s
1990s
2000s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
393,639 126,302 267,337 8,955 19,535 110,584 128,263 110,720 39,337 121,065
326,513 116,743 209,770 3,389 6,878 97,342 102,161 127,374 28,685 72,719
625,393 172,577 452,816 12,729 14,408 162,107 263,571 327,434 30,762 129,275
1980-2009 1,345,546 415,623 929,923 25,072 40,821 370,034 493,995 565,528 98,785 323,059
Region
1980s
1990s
2000s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
361,621 113,397 248,224 8,745 14,244 106,805 118,430 92,889 34,275 112,179
298,155 105,567 192,587 3,308 5,702 86,501 97,076 117,484 27,970 69,453
555,279 149,908 405,371 11,987 13,091 136,713 243,580 284,811 28,499 119,897
Region
1980s
1990s
39,364 12,630 26,734 895 1,954 11,058 12,826 11,072 3,934 12,106
32,651 11,674 20,977 339 688 9,734 10,216 12,737 2,869 7,272
2000s 62,539 17,258 45,282 1,273 1,441 16,211 26,357 32,743 3,076 12,928
1980-2009 44,852 13,854 30,997 836 1,361 12,334 16,467 18,851 3,293 10,769
Region Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
Region
1980s 1.8 0.1 2.4 -21.7 -8.4 1.4 6.5 5.5 -2.0 1.7
1990s -2.9 4.6 -6.3 -1.7 -7.4 -5.0 -7.8 -4.6 -5.5 -2.5
2000s 11.9 5.4 14.4 22.4 1.8 16.8 15.3 13.8 2.8 8.5
Note: Deflated with PPI base 2005 Source: GFI and AfDB staff estimates
1980s 36,162 11,340 24,822 874 1,424 10,681 11,843 9,289 3,428 11,218
1990s 29,815 10,557 19,259 331 570 8,650 9,708 11,748 2,797 6,945
2000s
1980-2009
55,528 14,991 40,537 1,199 1,309 13,671 24,358 28,481 2,850 11,990
40,502 12,296 28,206 801 1,101 11,001 15,303 16,506 3,025 10,051
Real Logarithmic Growth
Real Logarithmic Growth Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
1,215,055 368,873 846,183 24,040 33,037 330,019 459,086 495,184 90,744 301,529
Average Normalized IFFs
Average Non-normalized IFFs Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
1980-2009
1980-2009 2.5 1.8 2.6 2.4 -1.5 1.7 3.8 5.7 -1.2 0.6
Region Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
1980s 3.6 1.9 4.1 . 5.8 0.6 10.8 21.3 3.4 4.1
1990s -3.6 5.7 -7.9 . -12.6 -7.7 -8.3 -4.5 -5.3 -2.3
2000s
1980-2009
12.4 5.9 14.8 . 1.8 21.4 14.7 13.8 -0.1 7.0
2.4 1.8 2.5 . 0.0 0.7 4.3 7.8 -0.9 0.7
Note: Deflated with PPI base 2005 Source: GFI and AfDB staff estimates
Over the three decades ending 2009, real cumulative illicit outflows from Sub-Saharan Africa considerably outstripped those from North Africa. The Sub-Saharan Africa flows were more than twice those from North Africa. Chart 4 shows that three regional exporters of illicit capital from Africa account for 95 percent of cumulative outflows over the period 1980-2009; they are West and
24
African Development Bank and Global Financial Integrity
Central Africa at US$494.0 billion (37 percent), North Africa at US$415.6 billion (31 percent), and Southern Africa at US$370.0 billion (27 percent). These findings on the regions that are the largest exporters of illicit capital are consistent with findings in the previous GFI study on Africa.4 Further, the results from the North Africa region are also consistent with recent work (Ndikumana and Boyce, 2012), which estimates the capital flight from four North African countries over the period 1970-2010 to be US$454 billion.5
Chart 4. Distribu.on Illicit of Real Non-‐ Flows, Chart 4. Distribution of Real Non-normalized Financial normalized I llicit F inancial F lows, Cumulative 1980-2009 (in percent) Cumula.ve 1980-‐2009
31%
37%
27% North Africa
Horn of Africa
Great Lakes
2% 3% Southern
West & Central
Source: GFI and AfDB staff estimates
Similar to the previous GFI study, the Great Lakes region and the Horn of Africa together account for a small proportion (5 percent) of total outflows from the continent, implying that this region is a minor player in the overall flight of illicit capital from Africa. An important caveat to these findings is that regional outflows may be understated due to countries with missing data (for example, missing or incomplete data from Somalia and Eritrea may understate illicit outflows from the Horn of Africa, which thereby overstate the relative contributions of other regions. Further work needs to be undertaken to ascertain the low volume of illicit outflows from this region. Considering estimates at the country-level, the large outflows from: (i) West and Central Africa are driven largely by Nigeria, the Republic of Congo, and Cote d’Ivoire in that order of magnitude, (ii) North Africa are driven by outflows from Egypt, Algeria, and Libya in that order, and (iii) Southern Africa are mainly driven by South Africa, Angola, and Zimbabwe. Kar, Dev, and Devon Cartwrigh-Smith. Illicit Financial Flows from Africa: Hidden Resource for Development. Washington DC: Global Financial Integrity, (2010). 5 In addition to slight differences in methodology, Ndikumana and Boyce’s (2012) sample of North African countries is smaller then the sample in this study. Furthermore, the sample period in Ndikumana and Boyce (2012) is also longer than our study. 4
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
25
iii. Estimating the Severity of Illicit Flows We now turn our attention to the severity of illicit financial flows from the countries to control for other factors including GDP size, population, external debt, and ODA among others. Here, we seek to rank the relative severity of the problem of illicit flows for African countries based on six different indicators, namely, the volume of outflows, illicit flows to GDP, illicit flows to external debt, illicit flows to official development assistance (ODA), illicit flows to population, and illicit flows to non-oil exports.
a. Volume of Outflows The first indicator of the relative severity of the problem of illicit flows is the volume of outflows. Chart 5a ranks the top 20 African countries with the largest (nominal non-normalized) cumulative illicit outflows over the period 1980-2009. The chart shows that Nigeria, South Africa, and Egypt are the three largest exporters of illicit capital from Africa. In the following sections, we investigate how the countries with the largest nominal flows fare in terms of GDP and other indicators.
b. Illicit Flows to GDP In fact, the rankings of illicit flows as a percent of GDP in Chart 5b look quite different with Liberia, Djibouti, the Republic of the Congo, Equatorial Guinea, Seychelles, Chad, Lesotho and The Gambia
Chart 5a. Top 20 Countries’ Cumulative Non-normalized Illicit Chart Chart 5a. Top 20 Countries' Cumula6ve 5a. Top 20 Countries' Cumula6ve Financial Flows, 2000-2009 Non-‐normalized Illicit FIllicit inancial Flows, F lows, Non-‐normalized Financial 2000-‐2009 2000-‐2009 (in millions of U.S. dollars)
(in millions f U.S. doollars) (in moillions f U.S. dollars)
0
Chart 5b. Top 20 Countries’ Average Non-normalized Illicit Chart Chart op 20 Countries' Average Non-‐normalized 5b. Top 20 Countries' Average Non-‐normalized 5b. TIllicit Financial Flows, 1980-2009 FIllicit inancial Flows, F1 980-‐2009 Financial lows, 1980-‐2009 (as percent percent of G (as ofDP) GDP) (as percent of GDP)
0
100,000 100,000 150,000 150,000 200,000 200,000 250,000 250,000 0 50,000 50,000
0 5
Nigeria Nigeria
DjibouN DjibouN
South Africa South Africa
Congo, RCongo, epublic Roepublic f of
Egypt Egypt
Equatorial Guinea Guinea Equatorial
Algeria Algeria
Seychelles Seychelles
Libya
Chad
Libya
Lesotho Lesotho
Angola Angola
Gambia, Gambia, The The
Congo, RCongo, epublic Roepublic f of
Nigeria Nigeria
Cote d'Ivoire Cote d'Ivoire
Zambia Zambia
Cameroon Cameroon
Sao Tome and Principe Sao Tome and Principe
Liberia Liberia
Swaziland Swaziland
Ethiopia Ethiopia
Mauritania Mauritania
Gabon Gabon
Zimbabwe Zimbabwe
Zimbabwe Zimbabwe
Malawi Malawi
Botswana Botswana
Sierra Leone Sierra Leone
30 25
35 30
35
Cong
Equ
Sao TomS
Botswana Botswana Guinea Guinea
Zambia Zambia
Angola Angola
Equatorial Guinea Guinea Equatorial
Congo, Republic of, Eritrea, Liberia and Somalia were excluded from the rankings due missing and unreliable data. Chart 5e. Top 20 Ctoountries' Average Non-‐normalized Chart 5e. Top 20 Countries' Average Non-‐normalized
Chart Chart 5d. Top 20 Countries' Average Non-‐normalized 5d. Top 20 Countries' Average Non-‐normalized Source: GFI and AfDB staff estimates Illicit FIllicit inancial Flows, F1 980-‐2009 Financial lows, 1980-‐2009
Illicit FIllicit inancial Flows, F lows, Financial 1980-‐2009 1980-‐2009
(as percent of external debt) debt) (as percent of external
0
0 50
100 50
150 100
200 150
250 200
300 250
Equatorial Guinea Guinea Equatorial Botswana Botswana Namibia Namibia Nigeria Nigeria African Development Bank and Global Financial Integrity Swaziland Swaziland Chad
25 20
Namibia Namibia
Chad
Tunisia Tunisia
26
20 15
Gabon Gabon
Sudan Sudan
Note:
15 10
Chad
Morocco Morocco
Chad
10 5
Chad
350 300
350
(as percent of official evelopment asisstance) 1/ (as percent of odfficial development asisstance) 1/ 0 Libya
2,000 4,000 4,000 6,000 6,000 8,000 10,000 12,000 12,000 14,000 14,000 16,000 16,000 0 2,000 8,000 10,000
Libya
Equ
Nigeria Nigeria Equatorial Guinea Guinea Equatorial Gabon Gabon South Africa South Africa
Cong
ahead of Nigeria, which is ranked ninth. Illicit outflows from South Africa and Egypt are not among the top 20 when ranked in terms of GDP. However, analysis of illicit flows in terms of GDP may give the misleading impression that illicit flows are not an important issue for large countries with relatively higher GDPs. Even though illicit flows may be small in comparison to GDP, at times at less than 3 percent of GDP for some countries, policy makers are still very concerned about the problem of illicit flows and seek to curtail them. We now look to other “normalizers” such as non-oil exports, external debt, official development assistance (ODA), and population to give an indication of the extent of the problem for countries.
c. Illicit Flows to External Debt When illicit flows are ranked in terms of outstanding external debt (Chart 5d), countries with lower debt, such as Equatorial Guinea, Botswana, and Namibia are ahead of Nigeria, while South Africa and Egypt, the two largest exporters, are not among the top ten. Thus, a high IFF to external debt ratio does not necessarily imply that the country has a debt problem, that external debt was not utilized properly, or what some researchers have called a “revolving door” effect wherein increasing external debt merely ends up financing illicit capital outflows. Indeed, these results may also be misleading as the problem of illicit financial flows is magnified in countries with low debt.6
d. Illicit Flows to Official Development Assistance (ODA) Similarly, the ranking of the ratios of illicit flows to ODA (Chart 5e) also presents a problem in that it greatly understates the seriousness of the issue for Africa. The IFF to ODA ratio tends to be relatively low for African countries, not only because IFFs tend to be underestimated due to missing data but also because these countries are among the largest recipients of external aid. Nevertheless, for the region as a whole, in nominal terms, IFFs outpaced ODA by a factor of around 2 or 3 to 1 for most of the sample period. Indeed, this ratio was greatest in North Africa and West and Central Africa regions, at slightly more than 3 to 1 in the 1980s, declined a little in the 1990s, and rose again in the 2000s to well over 3 to 1. The ratio provides an indication of the extent to which illicit financial flows (IFFs) “offset” official development assistance (ODA) to developing countries. However, it is important to note that the IFF to ODA ratio is not an indicator of aid effectiveness, but rather an indication of “aid offset.” rather than aid effectiveness. Similar to several findings in this report, the results on the relationship between aid and illicit financial flows are indicative, and further analysis is necessary before a robust relationship can be established on the aid offsetting effects of illicit financial flows. Nonetheless, the issue of illicit financial flows is pertinent given that government budgets in donor
It was not possible to rank Democratic Republic of the Congo, Eritrea, Somalia or Liberia due to missing data on national accounts, balance of payments, and bilateral trade data. In addition, Libya was ranked on fewer than six indicators because data on external debt or official development assistance were missing.
6
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
27
Chart 5a. Top 20 Countries' Cumula6ve Non-‐normalized Illicit Financial Flows, 2000-‐2009
C
(in millions of U.S. dollars)
0
50,000
100,000
150,000
200,000
250,000
Nigeria South Africa
Congo
Egypt
Equa
Algeria
countries are under pressure as a result of the global economic as well as the subsequent European Libya Morocco crisis, and the ensuing lack of fiscal space implies that they may be unable to significantly expand Angola
ODA in the foreseeable future. Developing countries would to curtail illicit flows if they are to Congo, Republic need of Cote d'Ivoire reduce their offsetting effects on economic development (see Box 5).
Sao Tome
Cameroon Liberia
In 2009, illicit financial flows out of Africa were over threeEthiopia times the amount of ODA received. Hence, Gabon
curtailing illicit financial flows from African countries through Zimbabwe improvements in governance and the Botswana business climate can improve the productivity of both domestic and foreign capital needed to boost Sudan
economic growth.
Chad Tunisia Zambia
Chart 5c. Top 20 Countries’ Average Non-normalized Illicit Chart 5 c. T op 2 0 Countries' AFlows, verage Non-‐normalized Financial 1980-2009
normalized 25
30
Illicit Financial Flows, 1980-‐2009
(aspercent percent of non-oil (as of non-‐oil exports) exports)
35
normalized
0
500
1,000
1,500
2,000
(aspercent percent of external (as of external debt)
0
2,500 Equatorial Guinea
Congo, Republic of
Botswana
DjibouN
Namibia
Equatorial Guinea
Nigeria
Angola
Swaziland
Gambia, The
Chad
Algeria
DjibouN
Sierra Leone
Seychelles
Chad
Lesotho
Libya
Gabon
Mozambique
Zimbabwe
Gabon
South Africa
Cape Verde
Gambia, The
Seychelles
Congo, Republic of
Sao Tome and Principe
Rwanda
Ethiopia
Angola
50
100
150
200
C
debt) 250
300
350
Equatoria
Sou
Congo, Re
B
S
S
Cot
M
Rwanda
Malawi
Z
Lesotho
Ethiopia
C
Sudan
Cameroon
Egypt
MauriNus
Note: Congo, Republic of, Eritrea, Liberia and Somalia were excluded from the rankings due to missing and unreliable data. Chart 5f. Top 20 Countries' Average Non-‐normalized Source: GFI and AfDB staff estimates, IMF World Economic Outlook (WEO), World Bank.
Illicit Financial Flows per capita, 1980-‐2009 (in U.S. dollars) 1/
0
200
400
600
800
1,000 1,200 1,400 1,600
Seychelles Equatorial Guinea Gabon Libya Botswana Congo, Republic of Namibia DjibouN Swaziland South Africa MauriNus Angola Sao Tome and Principe
28
Chart 5d. Top 20 Countries’ Average Non-normalized Illicit Chart 5d. Top 20 Countries' Average Non-‐normalized Financial Flows, 1980-2009 Illicit Financial Flows, 1980-‐2009
Nigeria
nce) 1/
2,000 14,000 16,000
Equatorial Guinea
Algeria Bank and Global Financial Integrity African Development Gambia, The
Box 5: Curtailing Illicit Financial Flows as a Development Strategy The onset of the global financial crisis and, subsequently, the European Crisis brought about a decline in official development assistance (ODA) to Africa, both in terms of levels and as percent of GDP. Indeed ODA from members of the Development Assistance Committee (DAC) to Africa fell by US$7.5 billion from 2006 to 2007 and has yet to regain its pre-crisis level whether in terms of DAC General Government Revenue (Chart A) or in terms of African GDP (Chart B). Chart A. DAC ODA to Africa, 1980-‐2009
(as percent of DAfrica, AC General Chart A. DAC ODA to 1980-2009
(as percent of African GDP)
Chart A implies that taxpayers in DAC countries 8
0.7
have, for one reason or another, scaled back on
0.6
their tax dollars6 going towards bilateral loans
0.5
and grants that5 finance development assistance.
0.4
4 the importance of boosting This underscores
7
Percent
0.3
2
2009
2008
2007
2006
2005
2004
2003
2002
2001
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Source: Organization for Economic Cooperation and Development (OECD) and IMF World Economic Outlook (WEO)
retain more capital domestically. As long as the 0
2010
and reducing outflows of illicit capital in order to 1
0.1 0
3
domestic sources of savings and investments
0.2
2000
Percent
(as percent ofGovernment DAC GeneralRevenue) Government Revenue)
Chart B. inDAC ODA to Africa, 2000-‐2009 in The long-term decline DAC ODA represented
European economic crisis continues, large donors,
particularly European donors, will perhaps turn their economic policy focus inwards on domestic issues. Chart A shows that while the global financial crisis
has drawn our attention to this issue, it is not a recent occurrence because DAC ODA to Africa as a percent of DAC General Government revenue has fallen drastically since the mid-1980s.
8
rely0.7 more on domestic resources but to use those
7
resources more efficiently. The governments of 0.6
recover. In this context, the annual outflow of illicit assets from Africa becomes increasingly important from a policy perspective for both donors and
0
2010
indicator took a steep dip from which it has yet to
1 2009
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Africa’s 0 GDP increased until 2006, after which the
2
2008
B shows that DAC ODA to Africa as a percent of 0.1
3
2007
0.2
2006
domestic savings to finance their deficits. Chart
4
2005
coming under more pressure to tap
2004
0.3
5
2003
0.4 are base,
6 Percent
Percent
0.5 countries, especially those with a low tax those
2002
forced not only to
Chart B. DAC ODA to to Africa, Africa, 2000-‐2009 Chart B. DAC ODA 2000-2009 (as p ercent o f A frican GDP) (as percent of African GDP)
2001
(as percent of DAC General countries, African countries are Government Revenue)
2000
SinceChart Africa less ODA from DAC A. Dis AC receiving ODA to Africa, 1980-‐2009
Source: Organization for Economic Cooperation and Development (OECD) and IMF World Economic Outlook (WEO)
receivers of ODA.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
29
e. Illicit Flows to Population We now turn to the normalization of illicit financial flows by population. Table 3 presents ratios of cumulative illicit flows to end-decade population for each decade and the sample period (19802009) as a whole; average ratios are estimated based on annual IFF to population ratios over the period for20 which data is available. For the period as a whole, US$1,146 dollars per Chart 5b. Top Countries' Average Non-‐normalized Chart 5Africa c. Top 2lost 0 Countries' Average Non-‐normalized Chart 5b. Top 20 Countries' Average N1on-‐normalized Chart 5c. Top 20 Countries' Average N1on-‐normalized Illicit F inancial F lows, 980-‐2009 Illicit F inancial F lows, 980-‐2009 person. Despite aFdip in1980-‐2009 the 1990s, the per capita loss increasedIllicit from US$411 over the 1980s to Illicit Financial Financial Flows, 1980-‐2009 (as plows, ercent of GDP) (as percent of non-‐oil exports)
mula6ve 6ve al Flows, ws,
200,000 250,000 0,000 250,000
(as the percent of GDP) The loss of illicit capital per capita from North (as percent of non-‐oil exports) US$638 over 2000s. Africa over1,000 the period 19800 5 10 15 20 25 30 35 0 500 1,500 2,000 0 5 10 20 25 30 35 0 500 1,000 1,500 2,000 2009DjibouN (US$1,582) was 15 significantly higher than that from Sub-Saharan Africa (US$1,024). Although Nigeria
DjibouN Congo, Republic of Congo, REquatorial epublic of Guinea Equatorial Guinea Seychelles
Nigeria Congo, Republic of
Seychelles Chad Chad Lesotho
Equatorial Guinea Angola
2,500
2,500
the illicit financial flows in nominal terms from North Africa wasof argued to be similar to Ndikumana Congo, Republic DjibouN
DjibouN Guinea and Boyce (2012), the result in per capita terms differs on Equatorial account of the differences in the sample
of North African countries. Since Ndikumana and Boyce (2012) consider only four countries, the Angola Gambia, The
Lesotho Gambia, The Gambia, The Nigeria Nigeria Zambia
Gambia, The Algeria population would be considerably lower resulting in higher per capita results compared to this work
that considers nine countries in North Africa.
Zambia Sao Tome and Principe Sao Tome and Principe Swaziland
Algeria Sierra Leone Sierra Leone Chad
Chad Libya Libya Mozambique Mozambique Gabon
Within Sub-Saharan Africa, the per capita loss of illicit capital is mainly driven by Southern Africa
Swaziland Mauritania Mauritania Zimbabwe Zimbabwe Malawi
Gabon Cape Verde which has lost nearly $2,000 per person, while countries in West and Central Africa lost about Cape Verde Seychelles
US$1,293 exporters over the period 1980-2009 Malawi Sierra Leone per capita. The loss of illicit capital from fuelSao TSeychelles ome and Principe
Sierra Leone Gabon
Sao Tome and Principe
Ethiopia (US$1,631) is slightly more than three times the outflow per capita from nonfuel exporters (US$441). Gabon Namibia Namibia Botswana
Ethiopia Rwanda Rwanda Lesotho
Botswana Guinea Guinea Angola
Lesotho Sudan
Chart 5e. Top 20 Countries’ Average Angola Non-normalized Illicit Financial Flows, 1980-2009 Chart 5e. Top 20 Countries' Average Non-‐normalized (asIllicit percent of official Chart 5e. Top 20 Countries' Average on-‐normalized Financial FN lows, development
n-‐normalized malized 09
250 300 350 300 350
Illicit Financial Flows, asisstance) 1980-‐2009
(as percent o1980-‐2009 f official development asisstance) 1/ (as percent of official development asisstance) 1/ 0 Libya
0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000
Sudan Egypt Chart 5f. Top 20 Countries’ Average Egypt Non-normalized Illicit Financial Flows per capita, Chart 5f. Top 20 Countries' Average Non-‐normalized Chart 5f. TIllicit op 21980-2009 0 Countries' Average Non-‐normalized Financial Flows per capita, 1980-‐2009 Illicit F inancial Flows 980-‐2009 (in pUer .S. cdapita, ollars) 11/ (in U.S. dollars)
(in U.S. dollars) 1/
0 0 200 Seychelles Seychelles Guinea Equatorial
Libya Nigeria Nigeria Guinea Equatorial Equatorial Guinea Gabon
Equatorial Guinea Gabon
Gabon South Africa South Africa Algeria
Botswana Congo, Republic of Congo, Republic oNamibia f
Algeria Congo, Republic of Congo, Republic Botswana of Botswana Seychelles Seychelles Angola Angola Swaziland Swaziland Namibia Namibia Cote d'Ivoire Cote d'Ivoire Egypt Egypt MauriNus MauriNus Tunisia Tunisia Zimbabwe Zimbabwe Cameroon Cameroon Morocco Morocco Chad Chad
200 400
400 600
600 800
800 1,000 1,200 1,400 1,600 1,000 1,200 1,400 1,600
Gabon Libya Libya Botswana
Namibia DjibouN DjibouN Swaziland Swaziland South Africa South Africa MauriNus MauriNus Angola Angola Sao Tome and Principe Sao Tome and Principe Algeria Algeria Gambia, The Gambia, The Lesotho Lesotho Mauritania
Mauritania Egypt Egypt Nigeria Nigeria Chad Chad
Note: Congo, Republic of, Eritrea, Liberia and Somalia were excluded from the rankings due to missing and unreliable data. Source: GFI and AfDB staff estimates, World Bank, OECD
30
African Development Bank and Global Financial Integrity
The heavily indebted poor countries lost US$480 per person through illicit financial flows. Chart 5f presents twenty countries with the highest per capita loss in illicit outflows over the period 19802009. The results need to be considered in context as they may at times be a reflection of the population size. For example, Nigeria ranks 19th in the list of IFF/Population ratios due to its large population, yet Nigeria has a significant problem in curtailing massive outflows of illicit capital.
f.
Illicit Flows to Non-oil Exports
Illicit flows to non-oil exports provide another measure of the adverse impact that such flows have on African countries (reference Chart 5c). Non-oil exports, rather than total exports, are preferred because they facilitate the ranking of all countries based on a common denominator. On the other hand, outflows to total exports would understate the severity of illicit flows for oil exporters relative
Table 3. Africa: Non-Normalized Illicit Financial Flows Indicators, 1980-2009 (in U.S. dollars or ratios) Cumulative IFF/Decade-end Population ($ per capita) Group
1980s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern Africa West and Central Fuel-exporters Nonfuel-exporters HIPC
1990s 411.60 534.85 371.33 115.41 110.74 696.34 414.76 422.65 241.15 245.29
2000-2009 319.36 496.05 265.93 38.35 35.27 574.60 302.47 456.30 160.61 133.66
1980-2009
638.92 795.72 594.83 149.31 70.44 1,034.98 809.96 1,232.10 172.35 235.31
1,146.38 1,582.42 1,023.77 245.96 159.76 1,949.50 1,293.36 1,852.97 441.06 480.55
Average Non-normalized IFF/Decade-average Population ($ per capita) Group
1980s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern Africa West and Central Fuel-exporters Nonfuel-exporters HIPC
1990s 46.42 59.46 42.08 13.25 12.77 78.13 46.64 47.50 26.94 27.77
2000-2009 35.55 53.80 29.84 4.35 3.98 63.99 33.83 50.61 17.93 15.07
1980-2009 70.74 86.04 66.31 16.56 7.98 112.76 90.57 136.94 19.23 26.43
53.00 68.16 48.32 11.75 7.82 87.78 60.97 85.77 20.73 23.05
Cumulative Non-normalized IFF/ODA (ratio) Group
1980s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern Africa West and Central Fuel-exporters Nonfuel-exporters
1990s 2.08 1.95 2.14 1.14 0.55 3.73 2.47 4.70 0.91
2000-2009 1.25 1.67 1.09 0.26 0.16 1.72 1.29 5.26 0.47
1980-2009 2.15 3.69 1.86 0.57 0.21 2.86 2.68 6.58 0.40
1.84 2.41 1.67 0.57 0.26 2.59 2.21 5.95 0.52
Note: Deflated with PPI base 2005 Source: GFI and AfDB Staff Estimates.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
31
to other countries. There were some data issues in developing this measure because oil exports particularly in the earlier years were sometimes lumped in with exports of other hydrocarbons. Nonoil exports in years with missing oil export data were derived based on available data on average annual exports of oil to total exports. However, this measure still places Nigeria, Congo, Djibouti and Equatorial Guinea at the top of countries with high illicit financial flows.
Summary • On an inflation-adjusted basis, Africa lost between US$1.2-US$1.4 trillion over the 30-year period 1980-2009 through illicit financial flows, with illicit outflows from Sub-Saharan Africa outstripping those from North Africa by over two times. • In real terms, three African regions - West and Central Africa at US$494.0 billion (37 percent), North Africa at US$415.6 billion (31 percent), and Southern Africa at US$370.0 billion (27 percent)account for 95 percent of total cumulative illicit outflows from Africa over the 30-year period. • Estimates by country show that the large outflows from: (i) West and Central Africa are driven largely by Nigeria, the Republic of Congo, and Cote d’Ivoire, (ii) North Africa are driven by outflows from Egypt, Algeria, and Libya, and (i) Southern Africa are mainly driven by South Africa, Mauritius, and Angola. • Nigeria, South Africa, and Egypt are the three largest exporters of illicit capital from Africa based on volume of outflows. However, the relative severity of the problem of illicit flows among African countries can be assessed using several measures. We utilize other “normalizers” such as GDP, external debt, exports, official development assistance and population to gauge the extent of the problem.
32
African Development Bank and Global Financial Integrity
V. Net Resource Transfers
V
As defined at the outset of this report, net resource transfers (NRT) are estimated as the difference between net recorded transfers (NRecT) and unrecorded illicit financial flows. There are two ways of estimating net recorded transfers, namely the Narrow measure (based on net financial account balance) and the Broad measure (based on Narrow plus net current transfers, including workers’ remittances and migrant transfers and other current transfers plus net capital transfers, which includes debt write-offs and forgiveness and other capital account transfers of a non-monetary kind). Also, there are two methods of estimating illicit flows (Normalized and Non-normalized gross outflows). Accordingly, there are four alternative estimates of NRT using different permutations and combinations of recorded and unrecorded capital flows. Given the long time-span (30 years), we analyze developments in these four measures of NRT in real terms (i.e., estimates in current dollars are deflated by the U.S. 2005 PPI). The movements of these NRT estimates are shown in Chart 11. Estimates of real NRT show that regardless of whether we consider the Narrow or Broad measures of net recorded transfers (i.e., regardless of whether we take account of worker’s remittances and debt forgiveness as part of recorded transfers), Africa has been a net creditor to the rest of the world over the period 1980-2009 on a cumulative basis. The years in net loss of resources to the rest of the world outstrip those when it received resources by as much as two to one. Consequently, the cumulative NRT is negative no matter how we estimate recorded and unrecorded transfers. Obviously, the narrower the scope of recorded inflows and the broader the measure of illicit outflows, the more negative is NRT. That is, over the 30-year period 1980 to 2009, Africa provided net resources to the rest of the world which, on a cumulative basis, ranged from at least US$597 billion to as much as US$1.4 trillion. As it turns out, Africa was a net creditor to the world in all three decades no matter whether we use Narrow or Broad measure of recorded flows or the conservative or robust estimates of illicit outflows. The following analysis studies resource transfers resulting from recorded resource flows.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
33
Chart 6. Africa: Alternative Indicators of Real Net Resource Transfers: 1980-2009 (inChart billions of 2005 U.S. dollars) 6. Africa: Alterna7ve Indicators of Real Net Resource Transfers: 1980-‐2009 (in billions of U.S. dollars)
50
Billions of US dollars
0
-‐50
-‐100
-‐150
-‐200
Real NarrowNRTNon-‐norm
Real NarrowNRTNorm
Real BroadNRTNon-‐norm
Real BroadNRTNorm
Note: Deflated with PPI base 2005 Source: GFI and AfDB staff estimates
Chart 6 tracks movements in net resource transfers captured by these four measures in real terms—(i) NRecT Narrow net of non-normalized IFFs (NarrowNRTNon-norm), (ii) NRecT Narrow net of normalized IFFs (NarrowNRTNorm) ,(iii) NRecT Broad net of non-normalized IFFs ( BroadNRTNonnorm), and (iv) NRecT Broad net of normalized IFFs (BroadNRTNorm). Adjusted for inflation, NarrowNRTNon-norm yields the largest cumulative net resource transfers from Africa of US$1.38 trillion over the period 1980 to 2009, followed by NarrowNRTNorm at US$1.32 trillion, BroadNRTNon-norm at US$632.4 billion, and BroadNRTNorm at US$596.9 billion. NRT estimates vary widely depending upon whether we only account for the narrow measure of recorded transfers through the balance of payments (reflected in the financial account balance) or whether we consider the broadest measure of such recorded transfers, which also includes net current and capital transfers. Given the importance of transfers to African economies, it can be argued that broad measure of recorded transfers is more relevant and this would then be combined with non-normalized illicit financial flows so as not to underestimate illicit financial flows. Accordingly, even though there is a broad range of values for NRT, we consider BroadNRTNonnorm at US$632.4 to be plausible. All four measures of NRT, based on the NRecT Narrow and NRecT Broad measures, move in tandem and show that the largest net loss of resources occurred over the decade ending 2009 rather than in previous decades. This is because in the last decade ending 2009, not only do we see a larger volume of illicit outflows (no matter how we estimate them) but the financial account
34
African Development Bank and Global Financial Integrity
balance (representing NRecT Narrow) turned sharply negative meaning that Africa provided resources to, rather than received resources from, the rest of the world as recorded in the balance of payments. Only in 2009 do we see a sharp reversal when Africa turned from a net creditor to a net debtor, mainly due to the falloff in illicit outflows in the wake of the global economic crisis. The loss of net resources over the last decade as a whole was broadly shared between North Africa and Sub-Saharan Africa. In order to obtain a comprehensive overview of net resource transfers from Africa and its regions, a strong case can be made that we need to broaden not only the range of recorded flows through the balance of payments (because it makes little sense to exclude remittances and debt forgiveness for some African countries where these flows are very important) but also that we need to estimate unrecorded illicit outflows in a robust way (in order to offset an understatement of such flows due to missing data). Hence, we shall confine the analysis to the broadest measure of recorded transfers (NRecT Broad) and the most robust measure of illicit outflows (IFF Non-normalized). The resulting measure of NRT is captured by BroadNRTNon-norm. The ensuing discussion therefore focuses on BroadNRTNon-norm. Charts 7 and 9 show that there are differences in the evolution of net resource transfers from North Africa and Sub-Saharan Africa. Net resource transfers into North Africa became progressively worse throughout the three decades (according to the real BroadNRTNon-norm measure) declining from a net inflow of NRT (positive NRT) of about US$9.5 billion (cumulative) in the 1980s to an outflow of about US$1.7 billion in the 1990s before deteriorating significantly with NRT outflows of about US$270 billion in the decade to 2009. Sub-Saharan Africa, on the other hand, lost fewer resources in the 1990s relative to the two other decades, perhaps in part due to the positive effects of the structural adjustment program although it remained a net creditor to the world during the period as a whole (Chart 7). On a cumulative basis, Sub-Saharan Africa lost US$370.1 billion in net resources over the three decades ending 2009 compared to US$370.1 billion that was lost by North Africa (Chart 9). Charts 8 and 10 highlight the regional variations within Sub-Saharan Africa with regard to net resource transfers. Chart 10 shows that over the 30-year period and considering the cumulative amount, West and Central Africa lost the most resources on a net basis (US$246.7 billion), followed by Southern Africa (US$241.3 billion), while the Horn of Africa and the Great Lakes regions actually gained resources throughout the three decades.7 By analytical groupings, fuel exporters lost US$732.8 billion while non-fuel exporters actually registered a small gain (around US$48.1 billion) in net resources. The heavily indebted poor countries (HIPC) as a whole received net resources from the world to the tune of US$185.2 billion over the entire 30-year period. With the exception of a small loss of net terms for the Horn of Africa region in the 1980s.
7
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
35
Chart 7. Decennial Shifts in NRT, North Africa vs. Sub-Saharan Africa 7. Dof ecennial Shi7s in NRT, North Africa vs. Sub-‐Saharan Africa 1/ (inChart millions 2005 U.S. dollars) (in millions of U.S. dollars)
9,437 North Africa
-‐1,662
Sub-‐Saharan
-‐18,902
-‐270,030 -‐132,664 -‐218,555 -‐300,000
-‐250,000
-‐200,000
-‐150,000 1980s
Note:
-‐100,000
1990s
-‐50,000
0
50,000
2000s
1/ NRT is es5mated based on the broad measure of recorded transfers net of non-‐normalized illicit ouDlows adjusted for infla5on.
NRT is estimated based on the broad measure of recorded transfers net of non-normalized illicit outflows adjusted for inflation with PPI base 2005. Source: GFI and AfDB staff estimates
Chart 8. Decennial in NRT within Sub-Saharan Africa Africa 1/ Chart 8Shifts . Decennial Shi0s in NRT within Sub-‐Saharan (in millions of U.S. dollars) (in millions of 2005 U.S. dollars) -‐1,077
8,105 12,697
Horn of Africa
10,571
Great Lakes
-‐95,133
-‐36,445
-‐109,713
-‐200,000
Southern
-‐47,024 -‐30,507
-‐169,153 -‐150,000
-‐100,000
West & Central
-‐50,000 1980s
1990s
39,945 47,615
0
50,000
100,000
2000s
1/ NRT is es5mated based on the broad measure of recorded transfers net of non-‐normalized illicit ouDlows adjusted for Note:infla5on. NRT is estimated based on the broad measure of recorded transfers net of non-normalized illicit outflows adjusted for inflation with PPI base 2005. Source: GFI and AfDB staff estimates
36
African Development Bank and Global Financial Integrity
Chart 9. Distribution North AfricaNvs. Chart 9of . DCumulative istribu6on NRT, of Cumula6ve RT, Sub-Saharan North Africa Africa, 1980-2009 vs. Sub-‐Saharan Africa, 1980-‐2009 1/ (in millions of 2005 U.S. dollars)
(in millions of U.S. dollars)
North Africa
-‐262,255
Sub-‐Saharan
-‐370,121
-‐400,000 -‐350,000 -‐300,000 -‐250,000 -‐200,000 -‐150,000 -‐100,000 -‐50,000 Note:
0
1/ NRT is es3mated based on the broad measure of recorded transfers net of non-‐
NRT is estimated based on the broad measure of recorded transfers net of non-normalized illicit outflows adjusted for inflation normalized illicit ouBlows adjusted for infla3on. with PPI base 2005. Source: GFI and AfDB staff estimates
Chart 10.Chart Distribution of Cumulative within Sub-Saharan 10. Distribu/on of CNRT umula/ve NRT within Africa, Sub-‐Saharan 1980-2009 Africa, 1980-‐2009 1/ (in millions of 2005 U.S.(in dollars) millions of U.S. dollars)
19,724
Horn of Africa
98,130
Great Lakes
-‐246,684
Southern
-‐241,292
West & Central
-‐300,000 -‐250,000 -‐200,000 -‐150,000 -‐100,000 -‐50,000
0
50,000
100,000 150,000
1/ NRT is es5mated based on the broad measure of recorded transfers net of non-‐
NRT is estimated ibased the broad measure of recorded transfers normalized llicit oonuDlows adjusted for infla5on. net of non-normalized illicit outflows adjusted for inflation with PPI base 2005. Source: GFI and AfDB staff estimates Note:
It should be noted that the Ndikumana and Boyce (2008) finding that Sub-Saharan Africa was a net creditor to the world is supported by both the narrow and broad measures of recorded transfers net of normalized (conservative) or non-normalized (robust) methods of estimating illicit flows. This result holds despite some differences in methodology. For example, the estimates of trade misinvoicing in the Ndikumana and Boyce (2008) study are confined to African countries’ trade with industrial countries only. This is based on the assumption that industrial countries’ data are more
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
37
reliable than those of developing countries, and that misinvoicing in trade is basically carried out by developing non-industrial countries. While it is true that industrial countries’ databases are generally more reliable than those of developing countries largely because of larger statistical capacity, that does not mean that traders in industrial countries do not resort to trade misinvoicing. Indeed, Zdanowicz and Pak (2002) cite court cases in the United States confirming that traders resorted to deliberate trade misinvoicing. Moreover, serious governance issues in some advanced countries such as Greece, Italy, Portugal, and Spain show that one cannot safely assume that businesses in these countries do not resort to trade misinvoicing. Finally, increasing intra-developing country trade points to the need to capture emerging country trade flows and resulting misinvoicing between them. Indeed, for this reason, researchers such as Ajayi (1997) of the IMF estimate trade misinvoicing using trade between Nigeria and the world, not just industrial countries. Based on the Broad measure of net recorded transfers net of non-normalized illicit flows (BroadNRTNon-norm) adjusted for inflation, Chart 11 shows that Nigeria, Libya, South Africa, Algeria, and Angola were the top five losers of net resources on an inflation-adjusted cumulative basis while Morocco, Kenya, Ghana, Tunisia, and Tanzania were the top five gainers. For this group of top five gainers and losers, the volume of resources lost far outstripped the amount gained. The distribution of inflation-adjusted cumulative net resource transfers based on the Broad measure of recorded transfers net of non-normalized illicit flows across African countries is captured succintly in the heat map (Chart 12). It shows countries facing a large loss of net resource transfers in deep red (e.g., Algeria, Libya, Nigeria, South Africa), followed by fading shades of red representing countries where the loss is on a lower scale. Countries that have gained net resources (e.g., Kenya, Morocco, Tanzania, Tunisia, Ghana) are represented by deeper shades of blue.
38
African Development Bank and Global Financial Integrity
Chart 11. Asymmetrical Distribution of Cumulative Real Broad Net Resource Transfers, 1980-2009 (in millions of 2005 U.S. dollars)
Note:
Net resource transfers are derived by netting out non-normalized illicit flows (IFF Non-normalized) from net recorded transfers, broadly measured (NRecT Broad). Note: Deflated with PPI, base 2005 Source: GFI and AfDB staff estimates
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
39
Chart 12. Cumulative Real Net Resource Transfers, 1980-2009 (in millions of 2005 U.S. dollars)
Note:
NRT is estimated based on the broad measure of recorded transfers net of non-normalized illicit outflows adjusted for inflation with PPI base 2005. Note: Map Designed by Kyle Hunter Source: GFI and AfDB staff estimates
40
African Development Bank and Global Financial Integrity
Summary • Four alternative estimates of net resource transfers (NRT) were derived based on the narrow and broad recorded transfers net of normalized (or conservative) and non-normalized (or robust) estimates of illicit flows. The lowest NRT is given by narrowly measured recorded transfers (NRecT Narrow) net of robust illicit outflows (IFF Non-normalized). This is labeled NarrowNRTNonnorm. The highest NRT is given by broadly measured recorded transfers (NRecT Broad) net of conservatively estimated illicit outflows (IFF Normalized) which is labeled BroadNRTNorm. These four indicators of NRT move closely together over the period. • Over the 30-year period 1980-2009, Africa provided net resources to the world which, on a cumulative basis, ranged from at least US$597 billion to as much as US$1.4 trillion, depending upon the method of estimating NRecT and IFFs. This work argues that the broad measure of net recorded transfers coupled with non- normalized illicit financial flows (Broad NRT Non-norm) estimate of US$632.4 billion best describes the situation for African countries given their large dependence on remittance and capital transfers. • The BroadNRTNon-norm measure shows that Sub-Saharan Africa lost about US$108 billion more in resources on a net basis than North Africa did over the period 1980-2009 (Chart 9). However, the BroadNRTNon-norm indicator shows that in the most recent decade, North Africa lost some US$50 billion more than Sub-Saharan Africa (reference Appendix Table A.12). Also, net resource transfers into North Africa became progressively worse throughout the three decades. SubSaharan Africa, on the other hand, lost fewer resources in the 1990s relative to the two other decades, though it remained a net creditor to the world during the period as a whole. • Within Sub-Saharan Africa, West and Central Africa lost the most resources on a net basis over the 30-year period (US$246.7 billion), followed by Southern Africa (US$241.3 billion). By analytical groupings, fuel exporters lost US$732.8 billion while non-fuel exporters actually registered a small gain (around US$48.1 billion) in net resources. The heavily indebted poor countries (HIPC) as a whole received net resources from the world to the tune of US$185.2 billion over the entire 30year period. • Nigeria, Libya, South Africa, Algeria, and Angola were the top five losers of net resources on an inflation-adjusted cumulative basis while Morocco, Kenya, Ghana, Tunisia, and Tanzania were the top five gainers. These results are aligned with the results on net recorded transfers which shows that Libya, Algeria, and Angola were also among the top five losers of NRecT Broad while Morocco, Tunisia, Kenya, and Ghana were among the top five gainers of recorded transfers. • A heat map representing net resource transfers from African countries based on Broad NRecT net of robust illicit outflows captures the regional distributions.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
41
42
African Development Bank and Global Financial Integrity
VI. Policy Recommendations
VI
Our study shows that in spite of increasing recorded inward transfers through the balance of payments, most African countries experienced a net drain of resources over the 30-year period, 1980-2009, driven largely by illicit outflows. As a result, policies to curb this decline should focus on restricting the global absorption of illicit financial flows and curtailing the generation of these flows within Africa. For these initiatives to be effective, it is imperative that both African countries suffering from illicit financial flows and the developed countries absorbing these flows align their policies to address the issue. Lastly, we briefly suggest policies aimed at boosting net recorded transfers into Africa by improving the business climate.
i. Policies to Restrict the Absorption of Illicit Financial Flows This section discusses three initiatives aimed at stemming the absorption of illicit financial flows that can be undertaken both by African countries and the developed countries that absorb these flows: promoting a higher standard of transparency in the global financial system, facilitating the automatic exchange of tax information between countries, and signing double tax avoidance agreements.
a. Promote Transparency in the Global Financial System Recent work by GFI (e.g., Kar, Cartwright-Smith, and Hollingshead (2010)) has highlighted the role of offshore financial centers (“OFCs,” also called “tax havens” or “secrecy jurisdictions”) and banks in developed countries in facilitating the absorption of illicit capital from developing countries.8 Although issues related to opacity of tax haven operations have been brought to the forefront of public debate, less attention has been paid to the secrecy surrounding bank information particularly pertaining to private sector deposits of developing countries allegedly due to confidentiality requirements. Accordingly, we suggest two steps that should be taken to foster transparency in the financial system and stem the flow of illicit capital. First, banks and OFCs should be required to regularly report to the Bank for International Settlements (BIS) detailed deposit data by sector, maturity, and country of residence of deposit holders. Moreover, BIS must be permitted to widely disseminate this cross-border banking data for specific source and destination countries, enabling researchers to “map” non-bank private sector
Kar, Dev, Devon Cartwright-Smith, and Ann Hollingshead. The Absorption of Illicit Financial Flows from Developing Countries: 2002-2006 Washington DC: Global Financial Integrity, (2009).
8
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
43
deposits from, for instance, Nigeria into Switzerland. Ideally, this level of detail should be publicly available on the BIS website or, at least, to researchers by the BIS. Second, the obscurity of information on the beneficial ownership of companies, trusts, and other legal entities must be addressed at both domestic and international levels.9 At the domestic level in Africa, know-your-customer provisions in the laws governing financial institutions should be strengthened to make it illegal for banks and other financial institutions to open new accounts without knowledge of the natural person(s) owning the account(s) (i.e., its beneficial owners). Internationally, financial institutions in secrecy jurisdictions and developed countries should be required to collect information on the ultimate beneficial ownership of an account before accepting transfers into that account. African countries should support calls for G20 member states and other developed countries to create public registries of the true beneficial owners and controllers of corporations, limited-liability companies, and other legal entities. In cooperation with the G20, African countries should also urge the Financial Action Task Force (FATF) to institute a requirement for public availability of beneficial ownership information as part of Recommendations 24 and 25. Furthermore, they should insist that FATF Recommendation 10, requiring establishment of beneficial ownership as part of the customer due diligence process, is rigorously implemented by secrecy jurisdictions and developed countries—every jurisdiction should strengthen its anti-moneylaundering laws to explicitly require financial institutions to identify beneficial owners of accounts, disallow nominee corporations or disguised trusts from opening accounts, and ensure that these laws are properly monitored and enforced.
b. Automatic Exchange of Tax Information (AEI) Tax evasion is at the heart of the world’s shadow financial system and constitutes a significant component of illicit financial flows. One way to address the problem of tax evasion is for African countries to enter into automatic exchange of tax information (AEI) agreements with both developed countries and secrecy jurisdictions where the proceeds of tax evasion are lodged. Presently, the current OECD standard of information exchange “upon request” constrains the ability of national tax authorities to pursue tax evaders.10 In addition to stemming illegal capital flows, automatic information exchange contributes to domestic revenue collection efforts. The AEI agreements would require both countries’ governments to collect data from financial institutions on income, gains, and property of non-resident individuals, corporations, and trusts, and automatically provide that information to the governments where the non-resident entity is 9
A beneficial owner is a natural or real person who enjoys the financial benefits of ownership of a legal entity or account, even though title may be in another name or trust company. Any individual or group of individuals that, either directly or indirectly, has the power to vote, influence, or control transaction decisions regarding a specific security or other financial asset is a beneficial owner.
10
44
The “upon request” standard of tax information exchange requires tax authorities to submit detailed requests for information on specific taxpayers, which often requires authorities to know considerable prior information on the suspected tax evader and their transactions. Since tax evaders by nature hide their activities from the authorities, this can create a paradox where authorities need the information foreign governments have just to know what information they should request.
African Development Bank and Global Financial Integrity
located. We recommend that African governments focus on entering an AEI agreement with the European Union, the largest multilateral arrangement that has a well-functioning AEI system (the EUSTD). Moreover, they should also aggressively pursue agreements with the United States and other G20 governments. It is worth mentioning that tax authorities in some African countries are deeply plagued by corruption and, more importantly, lack resources and capacity. For instance, Kenya and Nigeria employ 3,000 and 5,000 tax and customs officials for populations of 32 and 140 million respectively, while the Netherlands employs 30,000 tax and customs officials for a population of 10 million. Therefore, in order for an African country to effectively implement an AEI agreement with the EU, United States, or other G20 government, it is imperative that the country also address corruption and capacity issues within its tax authority.
c. Double Tax Avoidance Agreements (DTAA) The establishment of AEI agreements between African and developed countries should be accompanied by signing double tax avoidance agreements (DTAAs), bilateral tax treaties designed to protect individuals and corporations from being taxed twice on the same income. More importantly, though, DTAAs set clear rules for each country’s ability to tax those entities and monitor compliance according to international norms, making it more difficult to evade taxes by moving income between the two countries. A DTAA also facilitates the exchange of tax payer information (and can include a provision for AEI), ensures a mutual assistance procedure for the resolution of disputes, and lays the groundwork for mutual assistance in pursuing recovery of taxes owed by either party to the agreement.
ii. Policies to Curtail Illicit Financial Outflows from Africa Previous work at GFI with macroeconomic models on developing countries such as India and Mexico suggests that the drivers of illicit financial flows fall into three broad classes— macroeconomic, structural, and governance-related. Accordingly, the appropriate policies to curtail illicit flows vary between countries depending on the extent of each class of driver. However, common features emerging from the countries studied in this report suggest African countries should focus on governance-related issues, an area in which the African Development Bank is actively engaged. This section discusses governance-related initiatives for both resource-rich and resource-poor countries to pursue.
a. Resource-Rich Countries In resource-rich countries, the natural resource sector is usually the main source of illicit financial flows (Ndikumana and Boyce (2011), Le Billon (2011)). For instance, according to the IMF, in 2002 alone, about US$4 billion from oil sales in Angola was not reported in national accounts. These countries generally lack the good governance structures that would enable citizens to monitor the amount and use of revenues from the natural resource sector. Often, rents and royalties derived from resource management are not used to support the social and economic development of Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
45
resource-rich countries but instead are embezzled or expended in unproductive ways through corruption and cronyism. Therefore, resource-rich countries should promote transparency and accountability through strengthening of civil society organizations and the implementation of open and transparent budgeting processes. Specifically, resource-rich countries should comply with the Open Budget Initiative under the leadership of the African Development Bank (see Box 6 below). Countries should also consider joining the Collaborative Africa Budget Reform Initiative (CABRI), another initiative supported by the African Development Bank, which provides a platform for African policymakers to exchange views and experiences on the best budgeting practices and procedures.
Box 6: The Open Budget Initiative The Open Budget Initiative is an international project developed in 1997 by the International Budget Partnership. Its objective is to assess and compare the level of fiscal transparency and accessibility of relevant budget information for citizens in relation to international best practices. It highlights the strengths and weaknesses of the specific country’s budget process. The methodology is based on a predetermined and uniform questionnaire consisting of 123 questions, out of which 92 assess public access to information and the remaining 32 questions are related to public participation in budget debates. The sum of the scores of answers to the questions provides an overall score which determines the ranking of each country. Finally, the government also undergoes a process of audit discussions. Twenty-seven countries have been analyzed by the Open Budget Initiative thus far. As of 2012, Equatorial Guinea, Chad, Algeria, Egypt, and Nigeria, largely resource-rich countries, remain in the bottom category, underlining the difficulty the populations of these countries face in accessing vital budget information they need to hold their governments accountable. Source: African Development Bank
Resource-rich countries should also adopt and comply with the Extractive Industries Transparency Initiative (EITI). EITI is an international initiative which ensures better governance in resource-rich countries through verification and full publication of payments made by companies and revenues received by governments from oil, gas, and minerals. The EITI standards are effective but exacting, and some countries find it difficult to commit to them due to a lack of capacity. In that regard, the African Development Bank is currently working on a technical assistance program for EITI implementation in several African countries including Chad, Sierra Leone, Guinea, Liberia, and Zambia. Going forward, resource-rich countries should look beyond EITI to ensure that good policies and practices are implemented along the entire resource value chain. Indeed, while great gains have been made through EITI, it addresses resource flows, which are only one part of the natural resource chain, and does not deal, for instance, with resource allocation processes. 46
African Development Bank and Global Financial Integrity
Resource-rich countries should also consider measures to ensure greater transparency and accountability over the way in which resources are accessed and the ultimate beneficial ownership of the companies benefitting from this access (Global Witness, 2013). In addition, there should be requirements for these companies to publish annual reports on their activities in African countries. Also, it is recommended that African countries receive assistance including from the ASLF to ensure that the upstream negotiation of contracts is fair. Further, resource-rich countries should set up well-functioning Sovereign Wealth Funds (SWFs) as we know that in theory, SWFs represent some “self-insurance” against capital flight that should favor autonomy in macroeconomic policy (Triki and Faye, 2011).
b. Resource-Poor Countries In resource-poor countries, illicit financial flows largely arise from the mispricing of trade by companies of all sizes. This activity is a form of money laundering and tax evasion. Indeed there appears to be a need for public sensitization on planned reforms which should be geared towards streamlining institutional performance and processes to improve transparency and tax collection and reduce corruption. While trade mispricing mainly involves corporate actors, government imports and exports can and often are manipulated by corrupt officials demanding bribes or kickbacks. Hence, resource-poor countries should focus on strengthening legal institutions and anti-corruption laws, and empowering regulatory agencies to exercise adequate oversight of the country’s financial system, imports and exports, multinational and domestic companies, and the collection of direct and indirect taxes. Domestic reforms needed to streamline institutional performance and behavior and to reduce corruption include tax reform and the creation of a national authority and management of public procurement. These include the following: • Tax reform: High tax burdens can lead to tax evasion and corruption, especially in situations of poor public service delivery. So tax reform based on a widening of the tax base and applicable to a broad group of taxpayers is not only fair but will ensure greater tax compliance than a proliferation of indirect taxes that are unwieldy to manage, costly to administer, and have large built-in incentives for evasion. The potential for further tax reform and rationalization (primarily through broadening the direct tax base and reducing the range of indirect taxes) should be explored in policy discussions between, on the one hand, the African Development Bank and its sister organizations and on the other hand, the Regional Member Countries. This will help to reduce the size of the underground economy, curtail illicit capital outflows, and improve overall governance. It is worth mentioning that the African Tax Administration Forum (ATAF) supported by the African Development Bank intends to overcome the lack of technical capacity of African tax administrations. Moreover, through this initiative member countries are increasingly made aware of tax evasion issues and educated on measures to better tackle them. In the same spirit, a technical assistance program is offered through a Global Tax Simplification Program (GTSP) of the World Bank and International Finance Corporation (IFC) on transfer pricing to equip African
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
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tax administrations with tools to better understand this issue and to be able to handle it. • Creation of a national authority for the regulation and management of public procurement: Policy measures needed to address bribes and kickbacks in government contracts include the creation of a national authority for the regulation and management of public procurement to ensure greater transparency and accountability in the contracting process. The procedures and rules for bidding on government contracts should be transparent, as should be information regarding the contracts awarded. African countries should follow international best practices in the area of government contracting so as to maximize public benefit. It is worth mentioning that many African countries (Benin, Cameroon, Niger, Senegal, etc.) have already set-up national entities in charge of the regulation and management of public procurement. However, most of them fail to achieve their goals due to a lack of independence and power to enforce. • Customs service reform: This involves the removal of ad-hoc exemptions from customs duties, streamlining clearance and document control procedures, and efficient computerization of payment and collection procedures in order to make procedures less cumbersome and more efficient. Additionally, capacity-building and training is essential to detect and investigate possible under- and over-invoicing of goods entering and leaving the country. • Anti-money laundering initiatives: Proceeds of drug trafficking, corruption, and tax evasion can be “laundered” through the use of complex financial structures involving the creation of shell corporations. During the last decade, many African countries have set-up anti–money laundering programs. Under these programs, financial institutions are required to report to relevant authorities (police and justice) suspicious transactions (above a threshold amount specified by regulation). Therefore, there is a need to strengthen the capacity of the relevant authorities to initiate appropriate legal actions. More broadly, anti-money laundering initiatives in the different countries need to be strengthened.
iii. Boosting Net Recorded Transfers by Improving the Business Climate Policies aimed at boosting recorded inward transfers generally involve measures that improve a country’s business climate ranging from political and economic stability to specific businessfriendly measures to improvements in infrastructure and corporate taxation and governance. The investment climate is the set of location-specific factors shaping the opportunities and incentives for firms to invest productively, create jobs, and expand. Government policies and behaviors exert a strong influence on the investment climate through their impact on costs, risks, and barriers to competition. However, these same policies to improve the business climate also tend to curtail illicit outflows. That said, the specific policy measures to boost recorded transfers and curtail unrecorded capital outflows can differ significantly depending upon the objectives of the policies and the sectors or agencies they target.
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Experience shows that progress can be made by addressing important constraints in a way that gives firms the confidence to invest—and by sustaining a process of ongoing improvements. In that regard, the Investment Climate Facility (ICF), an initiative supported by the African Development Bank to reduce the cost of doing business in Africa, is currently supporting several projects on investment climate reforms and engaging in consultations with African governments and private sectors on areas such as property rights and contracts, business registration and licensing, competition, the labor market, etc.
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VII
VII. Conclusions This study examined three key types of resource flows into an economy—financial and nonfinancial flows recorded in the balance of payments, unrecorded financial flows which are by definition illicit in nature, and a net of the two, which is defined as net resource transfers (NRT). We developed two types of recorded flows—a narrow measure corresponding to the net financial account balance and a broad measure defined as the sum of the narrow measure plus net capital and current transfers. Capital and current transfers include financial and non-financial transfers such as debt forgiveness and write-offs, remittances, and migrant transfers. In total, four alternative estimates of net resource transfers were developed combining narrow and broad measures of recorded transfers with normalized (conservative) and non-normalized (robust) illicit outflows. The lower estimate of NRT was derived by netting out conservatively estimated illicit outflows from broad recorded transfers while the higher estimate of NRT was obtained by netting out robust or non-normalized estimates of illicit outflows from narrow recorded transfers. No matter how NRT is defined, Africa provided net resources to the world on a cumulative constant dollar basis over the period 1980-2009 ranging from at least US$597 billion up to US$1.4 trillion. Net resource transfers out of poor developing countries can have a significant adverse impact on their economic development, but there is no unanimity among economists that the impact is significantly negative. This is perhaps because foreign capital is only one among several factors of production that drive economic growth in a complex manner. We did not explore whether net resource transfers helped or hindered economic growth or whether external resources helped maintain domestic social transfer programs. Rather, the focus was on estimating the pattern of net recorded transfers into and out of African countries and regions through the balance of payments and the estimation of unrecorded illicit outflows. This work did not consider the drivers of these flows, which would need to be analyzed in the context of detailed country studies. Illicit financial flows were the main driving force behind the net drain of resources from Africa because they grew at a much faster pace over the 30-year period 1980-2009 than the continent could attract net recorded transfers. The study found that in real terms, Africa lost between US$1.2 and US$1.3 trillion over the 30-year period 1980-2009 through illicit financial flows, which is about four times Africa’s total external debt.
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Over the 30-year period, Sub-Saharan African countries lost more resources than North African countries. (Using a measure based on broad net recorded transfers net of robust illicit flows (BroadNRTNon-norm) adjusted for inflation.) Sub-Saharan Africa lost about US$108 billion more than North Africa did over the 30-year period. Indeed, illicit flows from Sub-Saharan Africa outstrip those from North Africa by slightly more than two times over the first twenty years, although this was reversed in the last decade (2000-2009). Policy measures to curtail illicit financial flows include the following: (i) policy initiatives to restrict the absorption of illicit financial flows by international banks, such as the enhancement of transparency in the international financial system (which lifts the veil of secrecy surrounding OFCs, as well as bank transactions, and the opacity on beneficial ownership), automatic exchange of tax information and double taxation avoidance agreements; (ii) policies to curtail illicit financial outflows tailored to resource-rich and resource-poor countries such as the Open Budget Initiative, tax and customs service reforms, the creation of national authorities for the regulation and management of public procurement, as well as signing on to EITI and looking beyond this to ensure that policies are in place to facilitate greater transparency and accountability over the entire resource value chain; and (iii) policies to establish well-functioning sovereign-wealth funds and strengthening anti-money laundering laws and enforcement will also be important, as will be other policy measures to boost net recorded transfers by improving the business climate.
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References Aghevli, Bijan B., and Moshin S. Khan. Government Deficits and the Inflationary Process in Developing Countries, Staff Papers, International Monetary Fund, Vol. 25, No. 3, (1978). Ajayi, S. Ibi. An Analysis of External Debt and Capital Flight in the Severely Indebted Low Income Countries in Sub-Saharan Africa. International Monetary Fund Working Paper, No. 68 (1997). Ajayi, S. Ibi and Mohsin S. Khan, (ed.). External Debt and Capital Flight in Sub-Saharan Africa, International Monetary Fund, Washington DC (2000). Almounsor, Abdullah. A Development Comparative Approach to Capital Flight: The Case of the Middle East and North Africa, 1970-2002. In Capital Flight and Capital Controls in Developing Countries, by Gerald A. Epstein (ed.), Cheltenham, UK: Edward Elgar, (2006). Baker, Raymond. Capitalism’s Achilles Heel: Dirty Money and How to Renew the Free Market System. Hoboken, NJ: John Wiley & Sons, (2005). Beck, T., Maimbo, S. N, Faye, I. and Triki, T. Financing Africa through the Crisis and Beyond, World Bank Publication (2011). Brambila-Macias, Jose and Guido Cazzavillan. The Dynamics of Parallel Economies: Measuring the Informal Sector in Mexico, Research in Economics, No. 63 (2009). Brunner, Karl, and Allan H. Meltzer. Some Further Investigations of Demand and Supply Functions for Money, The Journal of Finance, Vol. 19, No. 2, Part 1: Papers and Proceedings of the Twenty-Second Annual Meeting of the American Finance Association, Boston, Massachusetts, (1963). Cerra, Valerie, Meenakshi Rishis, and Sweta Saxena. Robbing the Riches: Capital Flight, Institutions and Instability, IMF Working Paper 199, (2005). Chipalkatti N., Rishi. M. External Debt and Capital Flight in the Indian Economy, Oxford Development Studies. Vol. 29, No. 1, (2001). Collier, P.A. Hoeffler, and C. Pattillo. Flight Capital as Portfolio Choice, World Bank Economic Review. Vol. 15, No. 1. Washington, DC, (2001). Didszun, Klaus. On the Problem of Negative Net Financial Transfers to Developing Countries, Intereconomics. Vol. 25, No.2, (1990). Dooley, Michael P., and Kenneth M. Kletzer. Capital Flight, External Debt and Domestic Policies, NBER Working Paper (National Bureau of Economic Research), No. 4793 (1994). Dornbusch, Rudiger. Capital Flight: Theory, Measurement and Policy Issues, IADB Working Paper, No. 2 (1990). International Monetary Fund. Annual Report on Exchange Arrangements and Exchange Restrictions, Washington DC: IMF, (2010). Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
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International Monetary Fund. Balance of Payments and International Investment Position Manual. Sixth Edition (BPM6). Washington DC: IMF, (2009). International Monetary Fund. IMF Committee on Balance of Payments Statistics Annual Report 2010. Statistics Department, Washington DC: IMF, (2010). Isard, Peter, Leslie Lipschitz, Alexandros Mourmouras, and Boriana Yontcheva. The Macroeconomic Management of Foreign Aid: Opportunities and Pitfalls, International Monetary Fund. Washington DC , (2006). Kant, Chander. Foreign Direct Investment and Capital Flight, Princeton Studies in International Finance 80, (1996). Kar, Dev, and Sarah Freitas. Russia: Illicit Financial Flows and the Role of the Underground Economy, Washington DC: Global Financial Integrity (2013). Kar, Dev. Mexico: Illicit Financial Flows, Macroeconomic Imbalances, and the Underground Economy, Washington DC: Global Financial Integrity (2012). Kar, Dev. The Drivers and Dynamics of Illicit Financial Flows from India: 1948-2008. Washington DC: Global Financial Integrity (2010). Kar, Dev, and Devon Cartwrigh-Smith. Illicit Financial Flows from Africa: Hidden Resource for Development. Washington DC: Global Financial Integrity, (2010). Kar, Dev, Devon Cartwright-Smith, and Ann Hollingshead. The Absorption of Illicit Financial Flows from Developing Countries: 2002-2006 Washington DC: Global Financial Integrity, (2009). Kar, Dev, and Devon Cartwright-Smith. Illicit Financial Flows from Developing Countries: 2002-2006. Washington DC: Global Financial Integrity, (2008). Khan, Mohsin S., and Nadeem Ul Haque. Foreign Borrowing and Capital Flight: A Formal Analysis, IMF Staff Papers 32, (1985). Le, Quan V., and Paul J. Zak. Political Risk and Capital Flight, Journal of International Money and Finance 20, No. 4, (2006). Le, Quan, and Rishi Meenakshi. Corruption and Capital Flight: An Empirical Assessment, International Economic Journal 20, No. 4 (2006). Nandi, Sukumar. Capital Flight from India: Theory, Evidence and Determination, Journal of Foreign Exchange and International Finance. Vo. 8, No.4, (1995). Ndikumana, Leonce, and James, K. Boyce. New Estimates of Capital Flight from Sub-Saharan African Countries: Linkages with External Borrowing and Policy Options, Working Paper, Political Economy Research Institute, University of Massachusetts at Amherst., (2008). Ndung’u, Njuguna. Keynote Address By Governor, Central Bank of Kenya, Senior Policy Seminar on Implications of Capital Flight for Macroeconomic Management and Growth in Sub-Saharan Africa. Pretoria, South Africa, (2007). NGO Documents for the Earth Summit. Treaty 15: Capital Flight and Corruption, Non-governmental Organization Alternative Treaties at the Global Forum, (1992). Osterkamp, Rigmar. Is There a Transfer of Resources from Developing to Industrial Countries? Intereconomics. Vol.25, No.5, (1990).
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Pak, S. J. and J. S. Zdanowicz. U.S. Trade with the World: An Estimate of 2001 Lost U. S. Federal Income Tax Revenues due to Over-Invoiced Imports and Under-Invoiced Exports, Executive Summary to the U. S. Senate, (2000). Radelet, Steven. A Primer on Foreign Aid, Center for Global Development, Working Paper No.92 , (2006). Rajan, Raghuram and Arvind Subramanian. What Undermines Aid’s Impact on Growth?”, National Bureau of Economic Research, Inc. Working Paper, No. 11657, (2005). Reuter, Peter, (ed.). Draining Development? Controlling Flows of Illicit Funds from Developing Countries. World Bank, (2012). Schineller, Lisa M. An Econometric Model of Capital Flight from Developing Countries, Board of Governors of the Federal Reserve System (U.S.) International Finance Discussion Papers, No. 579, (1997) Schneider, Benu, Measuring Capital Flight: Estimates and Interpretations, Overseas Development Institute Working Paper, No. 194, (1997). Sheets, Nathan. Capital Flight from the Countries in Transition: Some Empirical Evidence, Journal of Policy Reform. Vol. 1, No. 3, (1996). Stern, Robert M. The Balance of Payments : Theory and Economic Policy, Chicago: Aldine Publishing Company, (1973). Triki, T. and Faye, I. Africa’s Quest for Development: Can Sovereign Wealth Funds Help?, African Development Bank Group Working Papers No 142, (2011). World Bank’s Investment Climate Surveys (ICS). World Bank. A Better Investment Climate for Everyone. In World Development Report: 2005, Oxford University Press, (2005).
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A
Appendix Ghana’s Balance of Payments Accounts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
List of Figures Unless otherwise indicated, sources are GFI and AfDB Staff estimates. Chart A.1. Africa: Percent of Countries Missing Data by Year, 1980-2009 . . . . . . . . . . . . . . . . . . . 61
List of Tables Unless otherwise indicated, sources are GFI and AfDB Staff estimates. Table A.1. Ghana: Balance of Payments, Standard Presentation, 2002-2006 . . . . . . . . . . . . . . . . 58 Table A.2. Countries with Missing Data for Net Recorded Transfers (NRecT) and Illicit Financial Flows (CED) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Table A.3. Net Recorded Transfers to and from Africa, 1980-2009 . . . . . . . . . . . . . . . . . . . . . . 62-63 Table A.4. Real Net Recorded Transfers to and from Africa, 1980-2009 . . . . . . . . . . . . . . . . . . 64-65 Table A.5. Net Recorded Transfers to and from Africa as a Share of GDP, 1980-2009 . . . . . . 66-67 Table A.6. Africa: Decennial Developments in Nominal NRT(NarrowNRTNon-norm) . . . . . . . . . . . 68 Table A.7. Africa: Decennial Developments in Nominal NRT(NarrowNRTNorm) . . . . . . . . . . . . . . . 68 Table A.8. Africa: Decennial Developments in Nominal NRT (BroadNRTNon-norm) . . . . . . . . . . . . 68 Table A.9. Africa: Decennial Developments in Nominal NRT(BroadNRTNorm) . . . . . . . . . . . . . . . . 68 Table A.10. Africa: Decennial Developments in Real NRT(NarrowNRTNon-norm) . . . . . . . . . . . . . . 69 Table A.11. Africa: Decennial Developments in Nominal NRT(NarrowNRTNorm) . . . . . . . . . . . . . . . 69 Table A.12. Africa: Decennial Developments in Real NRT (BroadNRTNon-norm) . . . . . . . . . . . . . . . 69 Table A.13. Africa: Decennial Developments in Real NRT (BroadNRTNorm) . . . . . . . . . . . . . . . . . . 69 Table A.14 Classification of Countries By Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
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Ghana’s Balance of Payments Accounts According to Stern (1973), “the balance of payments is a summary of all economic transactions between the residents of one country and the rest of the world, covering some given period of time.” The IMF’s more detailed definition is: “The balance of payments is a statistical statement that summarizes transactions between residents and nonresidents during a period. It consists of the goods and services account, the primary income account, the secondary income account, the capital account, and the financial account. Together, these accounts balance in the sense that the sum of the entries is conceptually zero.”11 Table A.1 presents the main accounts of Ghana’s balance of payments as reported by the country to the IMF for the period 2002-2006. The table illustrates the basic relationship between these accounts of the balance of payments reported by all countries mostly in accordance with the Balance of Payments Manual, Fifth Edition or BPM5 framework. The main point to note is that in theory the current account balance (which includes net current transfers) must offset net capital transfers and the financial account balance. To the extent that they do not, the discrepancies (due to errors in recording) are allocated to “Net Errors and Omissions”, a catch-all item that effectively balances the books. As the Sixth Edition of the Manual (BPM6) notes, each transaction involves a debit entry and a credit entry for each party to the transaction. This double-entry bookkeeping method ensures that the balance of payments must always balance. When these items do not balance due to errors in measurement and recording, the Net Errors and Omissions line captures this balance with a reverse sign so that the four main components add to zero (except for rounding errors). For the balance of payments to balance, entries must have the appropriate signs, positive or negative in the current, capital, and financial accounts.
Table A.1. Ghana: Balance of Payments, Standard Presentation, 2002-2006 (in millions of U.S. dollars) BOP Account A. Current Account of which: Net Current Transfers
2002
2003
2004
2005
2006
-105.1
123.7
566.9
-1,104.6
-1,040.2
826.9
1,244.9
1,579.9
1,794.2
2,248.3
B. Net Capital Transfers
73.3
154.3
251.0
331.2
229.9
C. Financial Account
-25.1
-230.7
200.6
747.8
636.0
D. Net Errors & Omissions
56.9
-47.4
115.2
25.6
174.2
A+B+C+D (BOP Check)
0.0
-0.1
-0.1
0.0
-0.1
Note: The last line of Table A.1 may not add to zero due to rounding. Source: Balance of Payments Statistics Yearbook 2007; Part 1: Country Tables, IMF
Reference, Robert M. Stern, The Balance of Payments, Aldine Publishing Company, Chicago, 1973, and Balance of Payments and International Investment Position Manual, Sixth Edition (BPM6), Draft, March 2007, International Monetary Fund, Washington, DC.
11
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As the 2007 Balance of Payments Statistics Yearbook notes:12 Under the conventions of the system, a compiling economy records credit entries (i) for real resources denoting exports and (ii) for financial items reflecting reductions in an economy’s foreign assets or increases in an economy’s foreign liabilities. Conversely, a compiling economy records debit entries (i) for real resources denoting imports and (ii) for financial items reflecting increases in foreign assets or decreases in foreign liabilities. In other words, for assets—whether real or financial—a positive figure (credit) represents a decrease in holdings, and a negative figure (debit) represents an increase. In contrast, for liabilities, a positive figure shows an increase, and a negative figure shows a decrease. Transfers are shown as credits when the entries to which they provide the offsets are debits and as debits when those entries are credits. Transactions are also of different types and the balance of payments must make room for recording them in a manner that is consistent across countries. That is a major raison d’être of the BPM6 and its predecessors—to ensure a framework of recoding different types of international transactions on a consistent basis across countries so that BOP statistics are meaningful for policymakers and researchers. Transactions can be either exchanges or transfers, monetary or non-monetary. As the BPM6 notes: An exchange involves a provision of something of economic value in return for a counterpart item of economic value. Purchases of goods and services, acquisition of assets, compensation of employees, dividends, etc., are all exchanges. An exchange is sometimes called a transaction with “something for something” or a transaction with a quid pro quo. A transfer involves a provision (or receipt) of an economic value by one party without receiving (or providing) a counterpart item of economic value. Taxes, debt forgiveness, grants, personal remittances are examples of transfers. A transfer is also called a transaction with “something for nothing” or a transaction without a quid pro quo. The estimation of NRecT involves all four kinds of external transactions (i.e., exchanges and transfers - either monetary or non-monetary) which are recorded in the various accounts of the balance of payments. The inclusion of transfers involving non-financial assets results in the terminology “Net Recorded Transfers” and not “Net Capital Transfers”. It is important to keep in mind that the reference to transfers here also includes exchanges. The balance of payments also accounts for certain non-financial, non-produced assets such as debt write-offs or write-downs. While these flows are not included in the financial account, they nevertheless involve a transfer of resources from the creditor to the debtor country. As noted earlier, every transaction can be either monetary or non-monetary in character. In the case of monetary transactions, one party makes a payment or receives a payment or incurs a liability or acquires an
Reference, 2007 Balance of Payments Statistics Yearbook, Annex V, page xxi, International Monetary Fund.
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asset. The medium of the transaction is in units of a currency. In contrast, non-monetary or nonfinancial transactions are not initially stated in units of currency although subsequently they may be. The BPM6 lists non-monetary transactions as barter transactions, remuneration or payments in kind, provision of goods and services without charge, foreign aid in goods, etc. Because the balance of payments registers all flows in monetary terms, all non-monetary transactions need to be valued appropriately (there are separate guidelines on valuation). Of course, entries in the balance of payments and other international accounts (such as the international investment position, IIP) can be either flows or stocks (also called positions). The guidance on the compilation of these accounts is provided with the overall objective of ensuring an integration of flows and positions. Flows refer to actions and events within an accounting period while stocks or positions refer to a level of assets or liabilities at a point in time. Integration between the two is meant to ensure that changes in stocks between two points in time are consistent with the recorded flows. In practice however, this consistency between stocks and flows may not hold due to differences in valuation during the accounting period arising from exchange rate variations, changes in the valuation of the assets, and other factors. Positions of external assets and liabilities are shown in the IIP. It should be noted that the BPM6 makes no distinction in the treatment of legal and illegal transactions which are defined as those “forbidden by law”. Now a transaction can be legal in the country of origin but not in the country of destination or vice-versa. For example, capital flight generated through bribery and kickbacks may be illegal in a country in Africa, but it may not be illegal to accept the deposits in say Switzerland. The transaction would be conceptually included in both the African country and in Switzerland because “Differences in the definition of illegal transactions between countries or within a country over time would cause inconsistencies in the international accounts if illegal transactions were to be omitted.” While such a recommendation would ensure consistency of treatment on a conceptual basis, in practice illegal transactions do result in discrepancies in balance of payments statistics. This is because they would tend to go unrecorded in the country of origin but recorded in the country of destination if the associated action there (i.e., taking the deposit) is not considered illegal. There are many other issues on which the BPM6 provides guidance to balance of payments compilers which are outside the scope of this paper. One such issue relates to the concept of residency. In general, the BPM6 defines residency of each party as the economic territory with which it has the strongest connection or the territory which is the center of predominant economic interest. For example, a multinational company may be registered abroad and may repatriate its profits to its parent company in a country where it is based but for balance of payments purposes, that company is to be considered as a resident in the country where it operates and with which it is effectively connected in terms of manpower, legal registration, ownership of land, generation of revenue, etc. We use two methods to estimate net recorded transfers from Africa and its various regions and groups. These are termed the NRecT Narrow and the NRecT Broad methods of estimation. 60
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Chart A.1. Africa: Percent of Countries Missing Data by Year, 1980-2009 Financial Account Balance Chart 1. Africa: Percent of Countries missing Data by Year, 1980-‐2009
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
16 14 12 10 8 6 4 2 0
1980
Percent
Financial Account Balance
Table A.2. Countries with Missing Data for Net Recorded Transfers (NRecT) and Illicit Financial Flows (CED) Time Period Missing Data Countries Algeria Angola Botswana Burkin Faso Burundi Central African Republic Chad Comoros Congo, Democratic Republic of Djibouti Equatorial Guinea Eriteria Gambia Guinea Guinea-Bissau Liberia Madagascar Mauritania Mozambique Namibia Sao Tome and Principe Somalia Zambia Zimbabwe
Net Recorded Transfers (Narrow) 1992-2004, 2010 1980-1984 1994-1999, 2010 1995-1999 1980-1984 1995-2010 1995-2010 1996-2010 1980-2010 1980-2010 1980-1985, 1997-2010 1980-1985,1997-2010 1998-2010 1980-2010 1980-1981, 1998-2000 1988-2003 2006-2010 1999-2010 1980-1989 1991-1996 1990-2010 1992-1996 1995-2010
Illicit Financial Flows (CED) 1992-2004, 2010 1980-1989, 2010 1995-1999, 2010 1995-1999 1980-1984 1995-2010 1995-2010 1996-2010 1980-2010 1980-1990 1980-2010 1980-1995, 2001-2010 1998-2002 1980-2010 1980-1981, 1994-2000 1988-2003 2006-2010 1999-2010 1980-1984 1980-1999, 2010 1991-1996 1990-2010 1992-1996 1995-2010
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
61
Table A.3. Net Recorded Transfers to and from Africa, 1980-2009 (in millions of U.S. dollars) Regions/Analytical Groups By Region: Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) North Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Sub-Saharan Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Horn of Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Great Lakes A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Southern A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) West and Central A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Note:
62
2000
2001
2002
2003
2004
34,051 8,530 -30,420 23,630 -1,907 -15,102 -35,022 -30,420 10,133
13,909 1,890 -20,567 8,205 -2,409 -6,936 -11,147 -20,567 -6,158
14,821 2,645 -5,978 19,771 -7,656 -8,095 -4,854 -5,978 4,961
15,531 3,526 -10,114 12,273 -1,447 -14,118 -4,782 -10,114 7,167
16,224 3,251 -23,660 13,957 -598 -22,045 -9,073 -23,660 -6,210
20,888 5,216 -39,562 10,824 5,785 -19,598 -28,462 -39,562 -18,862
40,301 47,080 55,142 61,274 55,342 13,036 36,090 5,457 6,319 7,875 -53,289 -103,998 -55,516 -46,194 54,681 26,337 27,816 37,252 42,700 37,163 5,017 11,791 3,631 -39,664 6,478 -25,388 -67,747 -12,003 16,458 8,450 -62,044 -74,848 -83,449 -65,687 -5,871 -53,289 -103,998 -55,516 -46,194 54,681 -766 -22,049 3,946 21,399 117,898
8,700 1,236 -1,671 1,545 128 -202 -2,962 -1,671 6,367
13,571 83 -25,239 10,104 -3,160 -5,020 -23,427 -25,239 -12,758
7,280 8,102 -113 -44 -12,608 -7,998 2,741 3,946 -443 81 -2,367 -480 -3,496 -4,616 -12,608 -7,998 -5,442 -5,044
8,158 79 -8,113 2,859 -592 -3,695 -2,291 -8,113 124
7,998 42 -18,879 4,500 -593 -6,153 -8,000 -18,879 -12,863
9,494 119 -20,443 4,170 693 -4,379 -10,327 -20,443 -15,442
15,387 106 -31,583 11,931 3,198 -7,017 -40,571 -31,583 -16,089
17,021 20,106 22,648 19,520 110 199 129 200 -49,994 -55,644 -51,819 4,696 22,139 19,367 15,564 13,821 -6,164 -5,019 -18,795 -3,965 -20,599 -12,957 3,015 4,430 -45,405 -57,520 -52,126 -9,913 -49,994 -55,644 -51,819 4,696 -32,863 -35,340 -29,042 24,417
2,496 60 6,185 892 77 4,976 -503 6,185 8,739
7,402 1,408 6,273 2,580 3,133 1,774 -2,300 6,273 14,674
20,480 8,448 -5,181 13,526 1,253 -10,082 -11,595 -5,181 22,891
6,629 6,719 2,003 2,689 -7,958 2,020 5,464 15,825 -1,966 -7,737 -4,569 -7,615 -7,652 -238 -7,958 2,020 -716 10,005
7,373 3,446 -2,001 9,414 -855 -10,424 -2,491 -2,001 7,043
8,225 3,209 -4,781 9,457 -5 -15,892 -1,073 -4,781 6,653
11,394 5,096 -19,119 6,654 5,092 -15,218 -18,135 -19,119 -3,420
24,914 12,930 -21,706 14,407 1,820 -18,371 -21,472 -21,706 15,323
30,059 35,036 38,626 35,822 35,979 5,258 6,190 7,675 -54,004 128 5,625 49,985 5,677 17,886 27,135 23,342 17,955 8,649 -20,869 10,443 -47,148 954 13,444 4,020 -29,443 -25,928 -13,561 4,043 -54,004 128 5,625 49,985 10,814 39,286 50,441 93,481
285 0 229 0 0 227 2 229 514
890 12 220 31 0 238 -49 220 859
1,912 1 981 139 0 554 263 981 2,488
977 0 345 28 0 365 -47 345 91
830 0 636 0 0 476 127 636 407
856 0 1,002 0 0 580 471 1,002 87
1,233 14 429 0 0 436 77 429 1,676
1,404 0 1,029 0 0 478 544 1,029 2,433
1,402 0 1,077 265 0 486 330 1,077 2,480
1,274 0 668 545 0 269 -190 668 1,941
3,387 0 1,066 222 0 226 537 1,066 4,453
872 5 1,401 40 0 840 6 1,401 2,278
2,423 470 1,054 262 -23 828 -397 1,054 3,947
3,334 2,001 999 1,039 -11 344 -890 999 6,334
2,086 603 1,288 755 -14 777 -403 1,288 3,976
1,903 1,190 354 550 7 121 -529 354 3,447
2,010 997 270 604 -1 -143 -334 270 3,278
2,507 957 -18 651 -19 389 -993 -18 3,446
3,062 747 446 572 -58 295 -557 446 4,255
3,391 686 3,076 1,335 -41 1,074 -247 3,076 7,153
4,014 10,350 -8,583 1,100 4 -8,730 -1,194 -8,583 5,781
4,522 1,426 2,308 2,147 23 2,302 -2,278 2,308 8,257
4,886 4,964 1,029 2,024 6,407 4,442 1,287 1,393 -24 11 2,910 4,443 202 -2,565 6,407 4,442 12,321 11,430
661 -63 490 143 -204 1,075 -635 490 1,086
1,745 210 2,778 664 3,040 102 -1,175 2,778 4,612
1,268 1,820 2,509 5,993 1,187 43 -5,755 2,509 5,544
659 836 742 728 -1,498 1,605 2,552 13,393 -2,493 -8,697 816 -4,399 -2,247 1,237 -1,498 1,605 -257 2,805
1,442 1,574 -3,816 5,243 -1,055 -4,214 -4,032 -3,816 -803
1,070 1,025 608 5,293 -170 -4,667 -232 608 2,704
974 1,890 -750 2,769 5,026 -1,391 -7,664 -750 2,113
565 3,053 -96 5,635 2,324 134 -8,845 -96 3,522
1,190 5,386 -5,452 -3,964 16,596 -7,874 -11,250 -5,452 1,124
1,940 1,155 4,721 4,578 6,756 4,175 -12,111 4,721 7,816
2,470 1,273 7,137 15,002 -17,311 18,052 -11,631 7,137 10,881
1,531 1,371 22,630 9,431 10,890 -200 -775 22,630 25,532
679 118 4,065 709 281 2,833 125 4,065 4,862
2,345 717 2,220 1,622 116 607 -680 2,220 5,256
13,966 4,626 -9,670 6,354 77 -11,023 -5,213 -9,670 8,525
2,908 659 -8,093 2,129 542 -6,526 -4,954 -8,093 -4,527
3,064 875 543 3,567 201 -6,647 1,404 543 4,482
3,414 1,213 -5,800 3,514 184 -12,051 74 -5,800 -1,173
5,955 2,459 -19,844 3,313 124 -14,601 -10,459 -19,844 -12,221
19,556 9,191 -25,764 7,171 -464 -20,065 -12,710 -25,764 2,169
23,581 20,243 -40,636 7,997 1,355 -30,813 -16,809 -40,636 1,967
25,186 2,677 -7,966 10,939 1,870 -5,749 -12,076 -7,966 18,761
26,975 3,888 -8,349 10,737 -3,534 -8,146 -1,750 -8,349 22,514
25,867 4,280 19,788 12,296 -459 -1,821 6,218 19,788 49,936
1980-1989
1990-1999
2000-2009
8,004 49 9,600 1,711 -291 7,693 -256 9,600 17,651
16,102 2,644 4,602 4,124 3,261 1,572 -5,262 4,602 21,041
5,508 -11 3,414 820 -368 2,717 247 3,414 8,912
3,150 771 -576 1,882 953 -3,813 -1,072 -576 3,346
2005
2006
2007
2008
4,295 0 430 109 0 628 -382 430 4,725
2009
3,459 0 3,125 221 0 1,599 1,164 3,125 6,584
Components of NRecT Narrow may not add to total due to the replacement of missing data with the negative current account balance. Components of NRecT Broad may not add to total (line A + line B + line C) due to the presence of missing data in one of the three lines. NRecT Broad is only calculated if all three components are present by year and by country.
African Development Bank and Global Financial Integrity
Table A.3. Net Recorded Transfers to and from Africa, 1980-2009 (in millions of U.S. dollars) Regions/Analytical Groups By Analytical Group: Fuel-Exporters A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Non-Fuel Exporters A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Heavily Indebted Poor Cnty. A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Note:
1980-1989
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
1990-1999
2000-2009
-561 -113 1,852 370 -129 1,852 635 2,854 2,179
1,335 54 -1,003 1,762 55 -1,003 -1,287 -504 1,172
10,529 1,860 -15,392 7,838 -3,134 -15,392 -24,803 -39,621 -27,232
1,360 -50 -8,134 2,548 -219 -8,134 -10,910 -25,447 -24,138
1,010 -67 -5,699 3,581 -538 -5,699 -747 -9,204 -8,261
1,099 17 -8,983 4,901 212 -8,983 1,631 -4,728 -3,611
9 83 -14,229 7,416 -382 -14,229 -5,621 -19,296 -19,204
667 644 -17,882 5,201 -1 -17,882 -17,367 -39,272 -37,961
17,820 7,352 -27,059 8,441 -2,090 -27,059 -45,083 -65,348 -40,177
20,983 10,562 -37,665 12,680 -5,386 -37,665 -57,246 -89,817 -58,272
20,668 38 -20,295 10,550 -2,612 -20,295 -61,375 -77,234 -56,529
21,275 12 -12,537 9,266 -16,157 -12,537 -58,296 -83,910 -62,623
20,396 11 -1,437 13,795 -4,168 -1,437 6,984 18,048 38,455
926 41 1,529 57 -23 1,529 -12 2,168 3,135
1,249 275 1,129 198 3 1,129 -96 2,138 3,643
1,573 2,383 -556 1,159 -37 -556 -593 1,491 5,447
640 750 928 413 29 928 -346 1,495 2,885
700 858 753 450 31 753 103 1,849 3,408
1,307 1,800 -315 914 99 -315 -522 619 3,726
1,011 1,008 648 852 9 648 -496 1,569 3,588
1,068 1,351 -311 803 -30 -311 -16 1,530 3,948
1,400 2,834 -1,574 823 9 -1,574 -42 1,540 5,774
1,792 9,089 -7,573 962 -94 -7,573 -394 -6,516 4,365
2,355 2,176 -171 2,270 -71 -171 -1,139 2,381 6,913
2,672 1,441 1,740 1,881 -176 1,740 -305 7,254 11,367
2,782 2,525 312 2,228 -175 312 -2,773 3,188 8,495
3,255 330 5,068 297 2 5,068 -110 5,877 9,036
4,636 1,270 3,975 1,052 -41 3,975 -464 5,440 11,051
10,758 6,457 46 6,236 128 46 -2,274 6,164 21,259
4,499 5,516 2,381 3,286 2,230 2,421 2,459 2,334 56 136 2,230 2,421 -1,228 -649 4,308 5,366 8,621 10,823
6,597 2,778 868 3,579 119 868 -1,739 4,926 11,954
9,083 4,305 933 3,990 56 933 -1,229 5,299 14,674
10,360 5,245 591 3,858 -40 591 -2,009 3,780 16,376
11,303 25,075 512 6,436 89 512 -1,480 7,208 22,000
13,776 4,867 -21,377 9,343 -17 -21,377 -3,681 -14,986 20,171
16,212 5,880 3,227 11,484 1,197 3,227 -4,303 12,816 30,322
15,569 14,661 7,058 3,698 3,912 7,139 8,959 9,916 -177 -138 3,912 7,139 -917 -5,509 15,914 17,014 38,007 39,641
Components of NRecT Narrow may not add to total due to the replacement of missing data with the negative current account balance. Components of NRecT Broad may not add to total (line A + line B + line C) due to the presence of missing data in one of the three lines. NRecT Broad is only calculated if all three components are present by year and by country.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
63
Table A.4. Real Net Recorded Transfers to and from Africa, 1980-2009 (in millions of 2005 U.S. dollars, deflated by PPI base) Regions/Analytical Groups By Region: Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) North Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Sub-Saharan Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Horn of Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Great Lakes A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Southern A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) West and Central A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Note:
64
2000
2001
2002
2003
2004
2005
33,022 8,378 -30,480 23,133 -1,549 -16,052 -33,504 -30,480 8,666
16,494 2,241 -24,390 9,730 -2,856 -8,225 -13,220 -24,390 -7,303
17,384 3,102 -7,012 23,190 -8,980 -9,495 -5,693 -7,012 5,819
18,644 4,233 -12,142 14,733 -1,737 -16,949 -5,741 -12,142 8,604
18,488 3,704 -26,962 15,905 -682 -25,121 -10,339 -26,962 -7,076
22,416 5,597 -42,457 11,616 6,208 -21,032 -30,545 -42,457 -20,243
40,301 13,036 -53,289 26,337 5,017 -25,388 -62,044 -53,289 -766
44,979 50,269 50,870 50,378 34,480 4,975 5,246 7,169 -99,358 -50,610 -38,351 49,777 26,575 33,960 35,450 33,829 11,265 3,310 -32,929 5,897 -64,725 -10,943 13,664 7,692 -71,509 -76,074 -54,534 -5,344 -99,358 -50,610 -38,351 49,777 -21,066 3,597 17,766 107,324
11,304 1,661 -2,300 1,989 161 -321 -3,908 -2,300 8,284
13,378 77 -24,634 9,715 -2,755 -5,149 -22,120 -24,634 -12,504
8,633 9,503 -134 -52 -14,953 -9,382 3,251 4,628 -525 95 -2,807 -563 -4,146 -5,415 -14,953 -9,382 -6,454 -5,917
9,793 95 -9,739 3,432 -711 -4,435 -2,751 -9,739 149
9,114 48 -21,513 5,128 -675 -7,011 -9,117 -21,513 -14,658
10,189 128 -21,939 4,475 743 -4,700 -11,083 -21,939 -16,572
15,387 106 -31,583 11,931 3,198 -7,017 -40,571 -31,583 -16,089
16,261 105 -47,764 21,151 -5,889 -19,680 -43,380 -47,764 -31,397
18,329 181 -50,727 17,655 -4,575 -11,812 -52,437 -50,727 -32,217
18,802 107 -43,020 12,922 -15,604 2,503 -43,275 -43,020 -24,111
17,769 182 4,275 12,581 -3,609 4,032 -9,024 4,275 22,227
3,780 88 9,635 1,345 115 7,823 -788 9,635 13,500
9,534 1,815 8,018 3,264 3,969 2,314 -2,927 8,018 18,846
19,644 8,302 -5,845 13,417 1,206 -10,903 -11,384 -5,845 21,169
7,861 7,881 2,375 3,154 -9,438 2,369 6,479 18,562 -2,331 -9,075 -5,418 -8,932 -9,074 -279 -9,438 2,369 -850 11,736
8,851 4,137 -2,402 11,301 -1,026 -12,513 -2,990 -2,402 8,454
9,373 3,657 -5,449 10,777 -6 -18,110 -1,223 -5,449 7,581
12,228 5,469 -20,518 7,141 5,464 -16,332 -19,462 -20,518 -3,670
24,914 12,930 -21,706 14,407 1,820 -18,371 -21,472 -21,706 15,323
28,718 31,940 34,374 4,794 -51,595 117 5,424 16,305 17,154 7,885 -45,045 869 -28,129 -23,637 -51,595 117 10,331 35,814
32,068 5,139 4,670 22,528 -17,326 11,161 -11,258 4,670 41,877
32,609 6,987 45,502 21,248 9,506 3,660 3,680 45,502 85,097
432 -1 356 0 0 353 4 356 788
1,147 16 279 39 0 305 -65 279 1,105
1,849 2 984 131 0 562 271 984 2,352
1,158 0 410 33 0 433 -56 410 108
974 0 746 0 0 558 149 746 478
1,027 0 1,203 0 0 697 566 1,203 104
1,405 16 489 0 0 497 88 489 1,910
1,507 0 1,104 0 0 513 584 1,104 2,611
1,402 0 1,077 265 0 486 330 1,077 2,480
1,217 0 638 521 0 257 -181 638 1,855
3,088 0 971 202 0 206 489 971 4,059
3,566 0 357 90 0 521 -317 357 3,923
3,149 0 2,845 202 0 1,455 1,059 2,845 5,993
1,326 7 2,175 62 0 1,306 15 2,175 3,507
3,109 604 1,381 332 -28 1,075 -505 1,381 5,094
3,318 1,977 907 1,030 -12 294 -886 907 6,202
2,474 715 1,527 895 -17 921 -478 1,527 4,715
2,232 1,396 415 645 8 141 -620 415 4,043
2,413 1,197 324 725 -1 -172 -401 324 3,935
2,857 1,090 -21 742 -22 444 -1,131 -21 3,927
3,286 802 479 613 -62 317 -598 479 4,566
3,391 686 3,076 1,335 -41 1,074 -247 3,076 7,153
3,835 9,889 -8,200 1,051 3 -8,341 -1,141 -8,200 5,523
4,123 1,300 2,104 1,958 21 2,098 -2,077 2,104 7,527
1,009 -100 783 220 -315 1,672 -966 783 1,690
2,251 269 3,507 820 3,839 166 -1,503 3,507 5,875
1,267 1,838 2,094 6,109 1,066 -484 -5,554 2,094 5,137
781 980 880 854 -1,777 1,883 3,026 15,709 -2,957 -10,201 968 -5,159 -2,665 1,450 -1,777 1,883 -305 3,290
1,732 1,890 -4,580 6,294 -1,267 -5,059 -4,840 -4,580 -964
1,220 1,168 693 6,032 -194 -5,318 -264 693 3,081
1,045 2,028 -805 2,972 5,394 -1,492 -8,225 -805 2,267
565 3,053 -96 5,635 2,324 134 -8,845 -96 3,522
1,137 5,146 -5,209 -3,787 15,855 -7,523 -10,748 -5,209 1,074
1,768 2,051 1,394 1,053 1,057 1,248 4,303 5,925 20,601 4,173 12,455 8,585 6,159 -14,371 9,914 3,806 14,987 -182 -11,040 -9,656 -705 4,303 5,925 20,601 7,125 9,033 23,242
1,014 181 6,321 1,062 429 4,493 160 6,321 7,515
3,027 926 2,852 2,074 158 768 -854 2,852 6,772
13,209 4,485 -9,829 6,146 153 -11,276 -5,216 -9,829 7,478
3,448 3,695 781 904 -9,598 -675 2,525 2,207 642 1,118 -7,740 -4,472 -5,875 -1,258 -9,598 -675 -5,369 3,924
3,678 1,050 652 4,282 241 -7,979 1,685 652 5,380
3,891 1,382 -6,609 4,004 210 -13,732 85 -6,609 -1,336
6,391 2,639 -21,296 3,556 133 -15,669 -11,224 -21,296 -13,115
19,556 9,191 -25,764 7,171 -464 -20,065 -12,710 -25,764 2,169
22,529 19,340 -38,823 7,640 1,295 -29,438 -16,059 -38,823 1,879
22,961 2,440 -7,262 9,972 1,705 -5,241 -11,009 -7,262 17,103
1980-1989
1990-1999
2000-2009
12,223 70 14,753 2,580 -454 12,045 -559 14,753 27,044
20,838 3,476 5,718 5,253 4,130 1,994 -6,835 5,718 27,129
8,443 -17 5,118 1,235 -568 4,222 229 5,118 13,544
2006
2007
2008
2009
4,056 4,519 854 1,842 5,319 4,043 1,069 1,268 -20 10 2,416 4,044 168 -2,335 5,319 4,043 10,229 10,404
22,395 3,228 -6,931 8,914 -2,934 -6,763 -1,453 -6,931 18,692
23,547 3,896 18,013 11,193 -418 -1,658 5,660 18,013 45,457
Components of NRecT Narrow may not add to total due to the replacement of missing data with the negative current account balance. Components of NRecT Broad may not add to total (line A + line B + line C) due to the presence of missing data in one of the three lines. NRecT Broad is only calculated if all three components are present by year and by country.
African Development Bank and Global Financial Integrity
Table A.4. Real Net Recorded Transfers to and from Africa, 1980-2009 (in millions of 2005 U.S. dollars, deflated by PPI base) Regions/Analytical Groups By Analytical Group: Fuel-Exporters A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Non-Fuel Exporters A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Heavily Indebted Poor Cnty. A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Note:
1980-1989
2000
2001
2002
2003
2004
2005
9,778 1,816 -15,578 7,756 -2,790 -15,578 -23,467 -38,558 -26,964
1,613 -60 -9,646 3,022 -260 -9,646 -12,939 -30,178 -28,625
1,185 -78 -6,685 4,200 -631 -6,685 -877 -10,796 -9,689
1,320 20 -10,784 5,883 255 -10,784 1,958 -5,675 -4,335
10 95 -16,214 8,451 -435 -16,214 -6,405 -21,989 -21,884
716 691 -19,190 5,582 -1 -19,190 -18,638 -42,146 -40,739
17,820 7,352 -27,059 8,441 -2,090 -27,059 -45,083 -65,348 -40,177
1,637 353 1,479 251 4 1,479 -130 2,774 4,740
1,546 2,365 -523 1,135 -28 -523 -573 1,452 5,363
759 889 1,101 490 34 1,101 -411 1,773 3,421
821 1,006 884 528 37 884 121 2,169 3,997
1,569 2,161 -378 1,097 118 -378 -626 743 4,472
1,152 1,149 738 970 10 738 -565 1,788 4,089
1,146 1,450 -334 861 -32 -334 -17 1,642 4,237
1,400 2,834 -1,574 823 9 -1,574 -42 1,540 5,774
1,712 8,683 -7,235 919 -89 -7,235 -376 -6,225 4,170
2,147 1,984 -156 2,069 -65 -156 -1,039 2,171 6,302
6,011 1,639 5,202 1,327 -52 5,202 -602 7,064 14,329
10,671 6,486 100 6,093 128 100 -2,256 6,069 20,812
5,335 6,471 2,823 3,855 2,645 2,840 2,916 2,738 66 160 2,645 2,840 -1,457 -761 5,109 6,294 10,224 12,694
7,920 3,335 1,042 4,296 143 1,042 -2,087 5,913 14,350
10,350 4,906 1,063 4,546 64 1,063 -1,400 6,038 16,722
11,118 5,629 635 4,140 -43 635 -2,156 4,056 17,574
11,303 25,075 512 6,436 89 512 -1,480 7,208 22,000
13,161 4,650 -20,423 8,926 -17 -20,423 -3,516 -14,317 19,271
14,779 5,360 2,942 10,470 1,091 2,942 -3,923 11,684 27,643
1990-1999
2000-2009
-921 -165 2,864 503 -204 2,864 804 4,162 3,075
1,686 69 -1,332 2,261 84 -1,332 -1,635 -655 1,455
1,415 56 2,366 85 -36 2,366 -13 3,349 4,821 4,975 491 7,903 465 4 7,903 -160 9,162 13,964
2006
2007
2008
2009
20,047 18,841 17,663 18,567 10,090 35 10 10 -35,984 -18,501 -10,408 -1,308 12,115 9,617 7,692 12,558 -5,146 -2,381 -13,414 -3,794 -35,984 -18,501 -10,408 -1,308 -54,692 -55,951 -48,397 6,358 -85,810 -70,409 -69,663 16,429 -55,673 -51,533 -51,990 35,006 2,218 1,196 1,445 1,561 -146 1,445 -253 6,022 9,437
2,533 2,298 284 2,028 -159 284 -2,524 2,902 7,733
12,926 13,346 5,859 3,366 3,248 6,499 7,438 9,027 -147 -126 3,248 6,499 -762 -5,015 13,212 15,488 31,553 36,085
Components of NRecT Narrow may not add to total due to the replacement of missing data with the negative current account balance. Components of NRecT Broad may not add to total (line A + line B + line C) due to the presence of missing data in one of the three lines. NRecT Broad is only calculated if all three components are present by year and by country.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
65
Table A.5. Net Recorded Transfers to and from Africa as a Share of GDP, 1980-2009 (in percent) Regions/Analytical Groups By Region: Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) North Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Sub-Saharan Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Horn of Africa A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Great Lakes A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Southern A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) West and Central A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Note:
66
1980-1989
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
1990-1999
2000-2009
1.9 0.0 2.3 0.4 -0.1 1.9 0.0 2.3 4.3
3.2 0.5 0.9 0.8 0.6 0.3 -1.0 0.9 4.2
3.3 0.8 -3.2 2.3 -0.2 -1.8 -3.2 -3.2 0.6
2.4 0.3 -3.5 1.4 -0.4 -1.2 -1.9 -3.5 -1.0
2.6 0.5 -1.1 3.5 -1.3 -1.4 -0.9 -1.1 0.9
2.7 0.6 -1.8 2.1 -0.3 -2.5 -0.8 -1.8 1.2
2.3 0.5 -3.4 2.0 -0.1 -3.2 -1.3 -3.4 -0.9
2.5 0.6 -4.7 1.3 0.7 -2.3 -3.4 -4.7 -2.2
4.1 1.3 -5.4 2.7 0.5 -2.6 -6.3 -5.4 -0.1
4.1 3.2 -9.1 2.4 1.0 -5.9 -6.6 -9.1 -1.9
4.2 0.4 -4.2 2.8 0.3 -0.9 -6.3 -4.2 0.3
3.9 0.4 -3.0 2.7 -2.5 1.1 -4.2 -3.0 1.4
3.7 0.5 3.7 2.5 0.4 0.6 -0.4 3.7 8.0
2.4 0.0 1.5 0.4 -0.2 1.1 0.1 1.5 3.8
2.9 0.4 -0.6 0.5 0.0 -0.1 -1.0 -0.6 2.1
2.3 0.0 -4.1 1.5 -0.4 -0.9 -3.4 -4.1 -2.1
2.3 0.0 -3.9 0.8 -0.1 -0.7 -1.1 -3.9 -1.7
2.6 0.0 -2.6 1.3 0.0 -0.2 -1.5 -2.6 -1.6
2.5 0.0 -2.5 0.9 -0.2 -1.1 -0.7 -2.5 0.0
1.9 0.0 -4.5 1.1 -0.1 -1.5 -1.9 -4.5 -3.0
1.8 0.0 -3.9 0.8 0.1 -0.8 -1.9 -3.9 -2.9
2.5 0.0 -5.0 1.9 0.5 -1.1 -6.5 -5.0 -2.6
2.4 0.0 -7.0 3.1 -0.9 -2.9 -6.3 -7.0 -4.6
2.4 0.0 -6.7 2.3 -0.6 -1.6 -7.0 -6.7 -4.3
2.4 0.0 -5.5 1.6 -2.0 0.3 -5.5 -5.5 -3.1
2.2 0.0 0.5 1.5 -0.4 0.5 -1.1 0.5 2.7
1.4 0.0 4.0 0.5 0.0 3.2 -0.2 4.0 5.4
3.6 0.7 3.0 1.2 1.4 1.0 -1.1 3.0 7.2
4.8 2.2 -2.0 3.5 0.2 -3.3 -3.0 -2.0 4.7
2.5 0.8 -3.0 2.1 -0.7 -1.7 -2.9 -3.0 -0.3
2.6 1.0 0.8 6.1 -3.0 -2.9 -0.1 0.8 3.9
3.0 1.4 -0.8 3.8 -0.3 -4.2 -1.0 -0.8 2.9
3.0 1.2 -1.8 3.5 0.0 -5.8 -0.4 -1.8 2.4
3.7 1.6 -6.2 2.1 1.6 -4.9 -5.8 -6.2 -1.1
6.9 3.6 -6.0 4.0 0.5 -5.1 -6.0 -6.0 4.3
7.1 8.5 -12.8 1.3 4.3 -11.2 -7.0 -12.8 2.6
7.0 1.1 0.0 3.6 1.7 0.2 -5.2 0.0 7.8
6.3 1.0 0.9 4.4 -3.4 2.2 -2.2 0.9 8.2
6.1 1.3 8.6 4.0 1.8 0.7 0.7 8.6 16.0
2.9 0.0 2.5 0.0 0.0 2.5 0.0 2.5 5.4
8.9 0.1 2.2 0.3 0.0 2.3 -0.5 2.2 8.6
11.6 0.0 6.4 0.8 0.0 3.8 1.8 6.4 13.4
11.0 0.0 3.9 0.3 0.0 4.1 -0.5 3.9 1.0
9.3 0.0 7.1 0.0 0.0 5.3 1.4 7.1 4.6
10.0 0.0 11.8 0.0 0.0 6.8 5.5 11.8 1.0
13.1 0.1 4.5 0.0 0.0 4.6 0.8 4.5 17.8
12.6 0.0 9.2 0.0 0.0 4.3 4.9 9.2 21.8
10.5 0.0 8.0 2.0 0.0 3.6 2.5 8.0 18.5
7.8 0.0 4.1 3.3 0.0 1.6 -1.2 4.1 11.9
16.2 0.0 5.1 1.1 0.0 1.1 2.6 5.1 21.3
15.3 0.0 1.5 0.4 0.0 2.2 -1.4 1.5 16.9
10.1 0.0 9.2 0.6 0.0 4.7 3.4 9.2 19.3
2.5 0.0 3.9 0.1 0.0 2.3 0.0 3.9 6.4
7.5 1.4 3.3 0.8 -0.1 2.6 -1.2 3.3 12.3
6.1 3.6 1.4 1.9 0.0 0.3 -1.6 1.4 11.2
6.0 1.7 3.7 2.2 0.0 2.2 -1.2 3.7 11.4
5.3 3.3 1.0 1.5 0.0 0.3 -1.5 1.0 9.5
5.4 2.7 0.7 1.6 0.0 -0.4 -0.9 0.7 8.8
6.2 2.4 0.0 1.6 0.0 1.0 -2.4 0.0 8.5
6.8 1.6 1.0 1.3 -0.1 0.7 -1.2 1.0 9.4
6.5 1.3 5.9 2.6 -0.1 2.1 -0.5 5.9 13.7
6.7 17.4 -14.4 1.8 0.0 -14.6 -2.0 -14.4 9.7
6.6 2.1 3.3 3.1 0.0 3.3 -3.3 3.3 12.0
6.0 1.3 7.9 1.6 0.0 3.6 0.2 7.9 15.2
5.9 2.4 5.3 1.7 0.0 5.3 -3.1 5.3 13.6
0.6 -0.1 0.5 0.1 -0.2 1.0 -0.6 0.5 1.0
1.0 0.1 1.6 0.4 1.8 0.1 -0.7 1.6 2.7
0.5 0.6 0.4 2.4 -0.1 -0.5 -1.7 0.4 1.5
0.4 0.4 -0.9 1.5 -1.5 0.5 -1.3 -0.9 -0.1
0.5 0.5 1.0 8.5 -5.5 -2.8 0.8 1.0 1.8
0.9 1.0 -2.5 3.4 -0.7 -2.7 -2.6 -2.5 -0.5
0.5 0.5 0.3 2.4 -0.1 -2.1 -0.1 0.3 1.2
0.3 0.7 -0.3 1.0 1.8 -0.5 -2.7 -0.3 0.7
0.2 0.9 0.0 1.7 0.7 0.0 -2.7 0.0 1.1
0.3 1.5 -1.5 -1.1 4.5 -2.1 -3.1 -1.5 0.3
0.5 0.3 1.1 1.1 1.6 1.0 -2.9 1.1 1.9
0.6 0.3 1.6 3.4 -3.9 4.1 -2.6 1.6 2.5
0.4 0.3 5.2 2.2 2.5 0.0 -0.2 5.2 5.8
0.8 0.2 4.2 0.8 0.4 2.8 0.0 4.2 5.2
2.5 0.8 2.4 1.7 0.1 0.8 -0.7 2.4 5.7
5.3 1.9 -4.7 2.6 0.2 -5.5 -2.4 -4.7 2.3
2.7 0.6 -7.6 2.0 0.5 -6.1 -4.6 -7.6 -4.2
3.0 0.7 -0.5 1.8 0.9 -3.6 -1.0 -0.5 3.2
2.4 0.7 0.4 2.8 0.2 -5.2 1.1 0.4 3.5
2.2 0.8 -3.8 2.3 0.1 -7.9 0.0 -3.8 -0.8
3.1 1.3 -10.4 1.7 0.1 -7.7 -5.5 -10.4 -6.4
8.5 4.0 -11.2 3.1 -0.2 -8.8 -5.5 -11.2 0.9
8.6 7.3 -14.8 2.9 0.5 -11.2 -6.1 -14.8 0.7
7.9 0.8 -2.5 3.4 0.6 -1.8 -3.8 -2.5 5.9
6.8 1.0 -2.1 2.7 -0.9 -2.1 -0.4 -2.1 5.7
7.7 1.3 5.9 3.6 -0.1 -0.5 1.8 5.9 14.8
Components of NRecT Narrow may not add to total due to the replacement of missing data with the negative current account balance. Components of NRecT Broad may not add to total (line A + line B + line C) due to the presence of missing data in one of the three lines. NRecT Broad is only calculated if all three components are present by year and by country.
African Development Bank and Global Financial Integrity
Table A.5. Net Recorded Transfers to and from Africa as a Share of GDP, 1980-2009 (in percent) Regions/Analytical Groups By Analytical Group: Fuel-Exporters A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Non-Fuel Exporters A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Heavily Indebted Poor Cnty. A. Net Current Transfers B. Net Capital Transfers C. Financial Account Balance Net FDI Net Portfolio capital Net Other Investments 1/ Reserve Assets, change Net Recorded Transfers Narrow ( C) Net Recorded Transfers Broad (A+B+C) Note:
1980-1989
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
1990-1999
2000-2009
-0.5 -0.1 1.7 0.4 -0.1 1.7 0.7 2.7 2.1
1.3 0.1 -0.8 1.8 0.1 -0.8 -1.1 -0.1 1.5
2.7 0.6 -5.8 2.7 -0.7 -5.8 -7.1 -13.1 -9.8
1.0 0.0 -6.1 1.9 -0.2 -6.1 -8.2 -19.2 -18.2
0.8 -0.1 -4.3 2.7 -0.4 -4.3 -0.6 -7.0 -6.3
0.7 0.0 -5.9 3.2 0.1 -5.9 1.1 -3.1 -2.4
0.0 0.0 -7.8 4.1 -0.2 -7.8 -3.1 -10.6 -10.6
0.3 0.3 -7.6 2.2 0.0 -7.6 -7.4 -16.7 -16.2
5.9 2.5 -9.0 2.8 -0.7 -9.0 -15.0 -21.8 -13.4
5.6 2.8 -10.1 3.4 -1.4 -10.1 -15.3 -24.0 -15.6
4.6 0.0 -4.5 2.4 -0.6 -4.5 -13.7 -17.3 -12.7
3.7 0.0 -2.2 1.6 -2.8 -2.2 -10.2 -14.7 -10.9
4.3 0.0 -0.3 2.9 -0.9 -0.3 1.5 3.8 8.0
3.7 0.2 5.8 0.2 -0.1 5.8 -0.1 8.3 12.1
4.2 1.0 3.8 0.7 0.0 3.8 -0.3 7.2 12.4
3.1 4.7 -0.7 2.2 0.0 -0.7 -1.0 3.1 10.9
2.4 2.8 3.5 1.5 0.1 3.5 -1.3 5.6 10.7
2.5 3.0 2.7 1.6 0.1 2.7 0.4 6.5 12.0
4.4 6.1 -1.1 3.1 0.3 -1.1 -1.8 2.1 12.6
2.9 2.9 1.9 2.4 0.0 1.9 -1.4 4.5 10.3
2.6 3.3 -0.7 1.9 -0.1 -0.7 0.0 3.7 9.5
2.7 5.4 -3.0 1.6 0.0 -3.0 -0.1 2.9 11.0
2.9 14.9 -12.4 1.6 -0.2 -12.4 -0.6 -10.7 7.2
3.5 3.2 -0.3 3.3 -0.1 -0.3 -1.7 3.5 10.2
3.4 1.8 2.2 2.4 -0.2 2.2 -0.4 9.2 14.5
3.6 3.2 0.4 2.8 -0.2 0.4 -3.5 4.1 10.9
3.4 0.3 5.0 0.3 0.0 5.0 -0.1 5.8 9.1
4.5 1.2 3.8 1.0 0.0 3.8 -0.5 5.2 10.7
6.2 3.9 0.1 3.4 0.1 0.1 -1.3 3.5 11.8
4.5 2.4 2.2 2.5 0.1 2.2 -1.2 4.3 8.7
5.4 3.2 2.4 2.3 0.1 2.4 -0.6 5.3 10.6
6.0 2.5 0.8 3.2 0.1 0.8 -1.6 4.5 10.8
7.1 3.3 0.7 3.1 0.0 0.7 -1.0 4.1 11.4
6.9 3.5 0.4 2.6 0.0 0.4 -1.3 2.5 10.9
6.7 14.8 0.3 3.8 0.1 0.3 -0.9 4.2 13.0
7.1 2.5 -11.1 4.8 0.0 -11.1 -1.9 -7.8 10.5
7.2 2.6 1.4 5.1 0.5 1.4 -1.9 5.7 13.5
5.7 2.6 1.4 3.3 -0.1 1.4 -0.3 5.8 13.9
5.4 1.4 2.6 3.6 -0.1 2.6 -2.0 6.3 14.6
Components of NRecT Narrow may not add to total due to the replacement of missing data with the negative current account balance. Components of NRecT Broad may not add to total (line A + line B + line C) due to the presence of missing data in one of the three lines. NRecT Broad is only calculated if all three components are present by year and by country.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
67
Table A.6. Africa: Decennial Developments in Nominal NRT(NarrowNRTNon-norm) (in millions of U.S. dollars or in percent)
Table A.7. Africa: Decennial Developments in Nominal NRT(NarrowNRTNorm) (in millions of U.S. dollars or in percent) Cumulative NRT
Cumulative NRT Region Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
1980s
1990s
2000s
-157,563 -185,786 -904,540 -46,843 -88,324 -411,698 -110,720 -97,462 -492,842 -3,460 -47 -2,753 -1,731 2,204 -3,960 -67,342 -46,531 -139,671 -38,187 -53,087 -346,457 -44,113 -84,402 -701,997 -5,789 -2,202 -12,627 -18,608 -226 -56,162
1980-2009 -1,247,888 -546,865 -701,023 -6,260 -3,488 -253,544 -437,732 -830,513 -20,618 -74,996
Region Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
1980s
1990s
2000s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-15,756 -4,684 -11,072 -346 -173 -6,734 -3,819 -4,411 -579 -1,861
-18,579 -8,832 -9,746 -5 220 -4,653 -5,309 -8,440 -220 -23
-90,454 -41,170 -49,284 -275 -396 -13,967 -34,646 -70,200 -1,263 -5,616
1980-2009 -41,596 -18,229 -23,367 -209 -116 -8,451 -14,591 -27,684 -687 -2,500
Table A.8. Africa: Decennial Developments in Nominal NRT (BroadNRTNon-norm) (in millions of U.S. dollars or in percent)
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-77,049 8,128 -85,177 -618 7,037 -61,381 -30,214 -50,861 3,882 12,979
Region
1980s
1990s
1980s
1990s
2000s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-14,081 -3,966 -10,115 -332 21 -6,494 -3,310 -3,292 -502 -1,645
-18,455 -9,909 -8,546 2 313 -3,873 -4,988 -9,582 -320 44
-87,113 -40,406 -46,707 -266 -268 -11,578 -34,595 -68,963 -1,304 -5,756
68
-7,705 813 -8,518 -62 704 -6,138 -3,021 -5,086 388 1,298
-1,446 -192 -1,254 634 3,113 -2,730 -2,271 -6,578 1,286 5,752
-1,196,491 -542,805 -653,686 -5,964 662 -219,448 -428,936 -818,371 -21,267 -73,561
1980-2009 -39,883 -18,094 -21,790 -199 22 -7,315 -14,298 -27,279 -709 -2,452
Table A.9. Africa: Decennial Developments in Nominal NRT(BroadNRTNorm) (in millions of U.S. dollars or in percent)
1980-2009 -579,556 -271,188 -308,367 19,254 87,558 -198,001 -217,178 -694,750 43,672 166,751
Region
1980s
1990s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-62,798 12,813 -75,610 -482 8,977 -58,976 -25,129 -39,664 4,647 12,643
-20,088 -465,602 -18,715 -279,255 -1,374 -186,347 6,487 12,412 32,056 50,674 -20,395 -85,433 -19,522 -164,000 -79,056 -565,746 11,846 26,518 56,633 93,385
Region
1980s
2000s
1980-2009 -548,488 -285,157 -263,331 18,417 91,708 -164,805 -208,651 -684,466 43,011 162,661
Average NRT
Average NRT Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-140,814 -184,552 -871,126 -39,660 -99,088 -404,057 -101,153 -85,463 -467,069 -3,323 17 -2,658 209 3,132 -2,680 -64,937 -38,732 -115,780 -33,103 -49,881 -345,952 -32,917 -95,821 -689,634 -5,025 -3,201 -13,041 -16,446 443 -57,557
1980-2009
Cumulative NRT 2000s
-14,462 -488,045 -1,920 -277,396 -12,542 -210,649 6,337 13,535 31,127 49,394 -27,298 -109,322 -22,708 -164,256 -65,780 -578,110 12,858 26,932 57,520 96,252
1990s
2000s
Region
Cumulative NRT 1980s
1990s
Average NRT
Average NRT Region
Region
1980s
2000s -48,805 -27,740 -21,065 1,354 4,939 -10,932 -16,426 -57,811 2,693 9,625
African Development Bank and Global Financial Integrity
1980-2009 -19,319 -9,040 -10,279 642 2,919 -6,600 -7,239 -23,158 1,456 5,558
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-6,280 1,281 -7,561 -48 898 -5,898 -2,513 -3,966 465 1,264
1990s -2,009 -1,871 -137 649 3,206 -2,040 -1,952 -7,906 1,185 5,663
2000s -46,560 -27,926 -18,635 1,241 5,067 -8,543 -16,400 -56,575 2,652 9,339
1980-2009 -18,283 -9,505 -8,778 614 3,057 -5,493 -6,955 -22,816 1,434 5,422
Table A.10. Africa: Decennial Developments in Real NRT(NarrowNRTNon-norm) (in millions of 2005 U.S. dollars or in percent)
Table A.11. Africa: Decennial Developments in Nominal NRT(NarrowNRTNorm) (in millions of 2005 U.S. dollars or in percent) Cumulative NRT
Cumulative NRT Region
1980s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
1990s
2000s
-246,138 -243,452 -892,251 -74,825 -115,120 -401,831 -171,313 -128,332 -490,420 -5,391 -153 -2,447 -2,754 2,811 -5,342 -104,196 -61,257 -140,144 -58,972 -69,734 -342,487 -70,740 -109,751 -680,809 -9,135 -3,055 -13,263 -28,459 -409 -57,865
Region
1980-2009
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-1,381,842 -591,776 -790,065 -7,992 -5,284 -305,597 -471,192 -861,300 -25,453 -86,732
1980s
1990s
2000s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-24,614 -7,482 -17,131 -539 -275 -10,420 -5,897 -7,074 -914 -2,846
-24,345 -11,512 -12,833 -15 281 -6,126 -6,973 -10,975 -305 -41
-89,225 -40,183 -49,042 -245 -534 -14,014 -34,249 -68,081 -1,326 -5,786
1980-2009 -46,061 -19,726 -26,336 -266 -176 -10,187 -15,706 -28,710 -848 -2,891
Table A.12. Africa: Decennial Developments in Real NRT (BroadNRTNon-norm) (in millions of 2005 U.S. dollars or in percent)
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-123,227 9,437 -132,664 -1,077 10,571 -95,133 -47,024 -81,605 5,583 19,560
1990s -20,564 -1,662 -18,902 8,105 39,945 -36,445 -30,507 -86,281 16,619 74,348
1980s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC Note:
-12,323 944 -13,266 -108 1,057 -9,513 -4,702 -8,161 558 1,956
1990s -2,056 -166 -1,890 811 3,994 -3,645 -3,051 -8,628 1,662 7,435
-219,739 -241,636 -860,268 -63,570 -128,522 -396,252 -156,169 -113,114 -464,015 -5,181 -72 -2,341 427 3,988 -4,024 -100,559 -51,426 -115,776 -50,855 -65,603 -341,874 -53,038 -124,035 -670,395 -7,772 -4,344 -13,974 -24,922 471 -59,405
1980s
1990s
2000s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-21,974 -6,357 -15,617 -518 43 -10,056 -5,086 -5,304 -777 -2,492
-24,164 -12,852 -11,311 -7 399 -5,143 -6,560 -12,404 -434 47
-86,027 -39,625 -46,402 -234 -402 -11,578 -34,187 -67,040 -1,397 -5,941
1980-2009 -1,321,643 -588,344 -733,298 -7,595 390 -267,761 -458,333 -847,468 -26,090 -83,856
1980-2009 -44,055 -19,611 -24,443 -253 13 -8,925 -15,278 -28,249 -870 -2,795
Table A.13. Africa: Decennial Developments in Real NRT (BroadNRTNorm) (in millions of 2005 U.S. dollars or in percent) Cumulative NRT
2000s -488,585 -270,030 -218,555 12,697 47,615 -109,713 -169,153 -564,864 25,845 91,287
1980-2009 -632,376 -262,255 -370,121 19,724 98,130 -241,292 -246,684 -732,750 48,047 185,195
Region Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
1980s
1990s
2000s
-100,672 -27,419 -468,817 16,847 -22,683 -274,946 -117,519 -4,735 -193,871 -867 8,293 11,340 13,752 41,121 48,932 -91,496 -27,749 -85,347 -38,908 -26,401 -168,795 -63,903 -102,931 -554,450 6,946 15,313 25,134 19,252 73,233 88,026
1980-2009 -596,908 -280,782 -316,126 18,766 103,805 -204,592 -234,104 -721,284 47,393 180,511
Average NRT
Average NRT Region
2000s
Region
Cumulative NRT 1980s
1990s
Average NRT
Average NRT Region
Region
1980s
2000s -48,858 -27,003 -21,856 1,270 4,761 -10,971 -16,915 -56,486 2,584 9,129
1980-2009 -21,079 -8,742 -12,337 657 3,271 -8,043 -8,223 -24,425 1,602 6,173
Region
1980s
1990s
2000s
Africa North Africa Sub-Saharan Horn of Africa Great Lakes Southern West&Central Fuel Non Fuel HIPC
-10,067 1,685 -11,752 -87 1,375 -9,150 -3,891 -6,390 695 1,925
-2,742 -2,268 -474 829 4,112 -2,775 -2,640 -10,293 1,531 7,323
-46,882 -27,495 -19,387 1,134 4,893 -8,535 -16,880 -55,445 2,513 8,803
1980-2009 -19,897 -9,359 -10,538 626 3,460 -6,820 -7,803 -24,043 1,580 6,017
The data in tables A.10-A.13 were deflated with PPI base 2005.
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
69
Table A.14 : Classification of Countries By Region Geograpical Regions Africa (53) North Africa (9) Algeria Dijibouti Egypt Lybia Mauritania Morocco Somalia Sudan Tunisia Sub-Saharan (44) Great Lakes (6) Burundi Congo, Democratic Republic of Kenya Rwanda Tanzania Uganda Horn of Africa (2) Eritrea Ethiopia Southern (14) Angola Botswana Comoros Lesotho Madagascar Malawi Mauritius Mozambique Namibia Seychelles South Africa Swaziland Zambia Zimbabwe West&Central (22) Benin Burkina Faso Cameroon Cape Verde Central African Republic Chad Congo, Republic of Cote d’Ivoire Equatorial Guinea Gabon Gambia, The, Ghana Guinea Guinea-Bissau Liberia Mali Niger Nigeria Sao Tome and Principe Senegal Sierra Leone Togo Source:
70
World Economic Outlook, IMF.
African Development Bank and Global Financial Integrity
Other Economic Groups Fuel (9) Algeria Angola Chad Congo, Republic of Equatorial Guinea Gabon Libya Nigeria Sudan Non Fuel Primary Commodity Exporters (12) Burkina Faso Burundi Central African Republic Congo, Democratic Republic of Guinea Guinea-Bissau Mali Mauritania Mozambique Sierra Leone Zambia Zimbabwe HIPC (33) Benin Burkina Faso Burundi Cameroon Central African Republic Chad Comoros Congo, Democratic Republic of Congo, Republic of Cote d’Ivoire Eritrea Ethiopia Gambia, The Ghana Guinea Guinea-Bissau Liberia Madagascar Malawi Mali Mauritania Mozambique Niger Rwanda Saotome and Principe Senegal Sierra Leone Somalia Sudan Tanzania Togo Uganda Zambia
Illicit Financial Flows and the Problem of Net Resource Transfers from Africa: 1980-2009
71
African Development Bank
Global Financial Integrity
15 Avenue du Ghana
1100 17th Street, NW,
P.O. Box 323-1002
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